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End of training

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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: apache-2.0
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+ base_model: unsloth/SmolLM-360M
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+ tags:
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+ - axolotl
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+ - generated_from_trainer
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+ model-index:
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+ - name: 000ff5d1-3128-436b-ab7d-5b00e638f8cf
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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+ <details><summary>See axolotl config</summary>
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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ adapter: lora
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+ base_model: unsloth/SmolLM-360M
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+ bf16: auto
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+ chat_template: llama3
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+ dataset_prepared_path: null
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+ datasets:
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+ - data_files:
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+ - 69c0cf05b23d085a_train_data.json
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+ ds_type: json
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+ format: custom
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+ path: /workspace/input_data/69c0cf05b23d085a_train_data.json
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+ type:
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+ field_input: eng
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+ field_instruction: darija
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+ field_output: darija_ar
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+ format: '{instruction} {input}'
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+ no_input_format: '{instruction}'
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+ system_format: '{system}'
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+ system_prompt: ''
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+ debug: null
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+ deepspeed: null
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+ device_map: auto
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+ do_eval: true
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+ early_stopping_patience: 3
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+ eval_batch_size: 4
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+ eval_max_new_tokens: 128
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+ eval_steps: 300
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+ eval_table_size: null
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+ evals_per_epoch: null
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+ flash_attention: true
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+ fp16: false
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+ fsdp: null
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+ fsdp_config: null
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+ gradient_accumulation_steps: 4
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+ gradient_checkpointing: false
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+ group_by_length: true
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+ hub_model_id: kk-aivio/000ff5d1-3128-436b-ab7d-5b00e638f8cf
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+ hub_strategy: end
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+ learning_rate: 0.0002
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+ load_in_4bit: false
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+ load_in_8bit: false
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+ local_rank: null
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+ logging_steps: 50
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+ lora_alpha: 64
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+ lora_dropout: 0.05
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+ lora_fan_in_fan_out: null
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+ lora_model_dir: null
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+ lora_r: 32
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+ lora_target_linear: true
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+ lr_scheduler: constant
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+ max_grad_norm: 1.0
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+ max_memory:
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+ 0: 75GB
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+ max_steps: 20953
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+ micro_batch_size: 4
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+ mlflow_experiment_name: /tmp/69c0cf05b23d085a_train_data.json
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+ model_type: AutoModelForCausalLM
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+ num_epochs: 10
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+ optim_args:
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+ adam_beta1: 0.9
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+ adam_beta2: 0.95
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+ adam_epsilon: 1e-5
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+ optimizer: adamw_bnb_8bit
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+ output_dir: miner_id_24
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+ pad_to_sequence_len: true
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+ resume_from_checkpoint: null
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+ s2_attention: null
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+ sample_packing: false
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+ save_steps: 300
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+ saves_per_epoch: null
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+ sequence_len: 512
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+ strict: false
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+ tf32: true
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+ tokenizer_type: AutoTokenizer
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+ train_on_inputs: false
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+ trust_remote_code: true
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+ val_set_size: 0.05
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+ wandb_entity: null
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+ wandb_mode: online
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+ wandb_name: a9eb9e07-4485-4d9d-b2a5-cd0e87c62301
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+ wandb_project: SN56-11
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+ wandb_run: your_name
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+ wandb_runid: a9eb9e07-4485-4d9d-b2a5-cd0e87c62301
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+ warmup_steps: 50
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+ weight_decay: 0.0
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+ xformers_attention: null
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+
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+ ```
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+
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+ </details><br>
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+
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+ # 000ff5d1-3128-436b-ab7d-5b00e638f8cf
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+
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+ This model is a fine-tuned version of [unsloth/SmolLM-360M](https://huggingface.co/unsloth/SmolLM-360M) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0163
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0002
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+ - train_batch_size: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 16
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+ - optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=adam_beta1=0.9,adam_beta2=0.95,adam_epsilon=1e-5
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+ - lr_scheduler_type: constant
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+ - lr_scheduler_warmup_steps: 50
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+ - training_steps: 20953
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | No log | 0.0002 | 1 | 3.1938 |
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+ | 0.2034 | 0.0582 | 300 | 0.1793 |
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+ | 0.1101 | 0.1164 | 600 | 0.1045 |
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+ | 0.0749 | 0.1747 | 900 | 0.0757 |
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+ | 0.0621 | 0.2329 | 1200 | 0.0644 |
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+ | 0.0515 | 0.2911 | 1500 | 0.0512 |
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+ | 0.0468 | 0.3493 | 1800 | 0.0436 |
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+ | 0.0479 | 0.4075 | 2100 | 0.0370 |
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+ | 0.0342 | 0.4657 | 2400 | 0.0335 |
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+ | 0.0347 | 0.5240 | 2700 | 0.0293 |
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+ | 0.0246 | 0.5822 | 3000 | 0.0356 |
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+ | 0.0305 | 0.6404 | 3300 | 0.0283 |
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+ | 0.0208 | 0.6986 | 3600 | 0.0317 |
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+ | 0.019 | 0.7568 | 3900 | 0.0231 |
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+ | 0.0157 | 0.8151 | 4200 | 0.0234 |
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+ | 0.0243 | 0.8733 | 4500 | 0.0233 |
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+ | 0.0231 | 0.9315 | 4800 | 0.0203 |
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+ | 0.018 | 0.9897 | 5100 | 0.0219 |
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+ | 0.0121 | 1.0479 | 5400 | 0.0199 |
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+ | 0.0142 | 1.1062 | 5700 | 0.0196 |
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+ | 0.0144 | 1.1644 | 6000 | 0.0186 |
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+ | 0.0118 | 1.2226 | 6300 | 0.0173 |
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+ | 0.013 | 1.2808 | 6600 | 0.0156 |
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+ | 0.0138 | 1.3390 | 6900 | 0.0163 |
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+ | 0.0093 | 1.3972 | 7200 | 0.0153 |
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+ | 0.0052 | 1.4555 | 7500 | 0.0158 |
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+ | 0.0106 | 1.5137 | 7800 | 0.0172 |
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+ | 0.0099 | 1.5719 | 8100 | 0.0163 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.13.2
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+ - Transformers 4.46.0
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+ - Pytorch 2.5.0+cu124
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
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