metadata
library_name: peft
license: apache-2.0
base_model: EleutherAI/pythia-410m-deduped
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 5e94c9e5-cf22-4b87-af86-7ba703fd4d51
results: []
See axolotl config
axolotl version: 0.4.1
adapter: lora
auto_find_batch_size: true
base_model: EleutherAI/pythia-410m-deduped
bf16: auto
chat_template: llama3
dataset_prepared_path: null
datasets:
- data_files:
- 819347714d90e9b5_train_data.json
ds_type: json
format: custom
path: /workspace/input_data/819347714d90e9b5_train_data.json
type:
field_instruction: premise
field_output: hypothesis
format: '{instruction}'
no_input_format: '{instruction}'
system_format: '{system}'
system_prompt: ''
debug: null
deepspeed: null
do_eval: true
early_stopping_patience: 3
eval_max_new_tokens: 128
eval_steps: 50
evals_per_epoch: null
flash_attention: true
fp16: false
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: false
group_by_length: true
hub_model_id: lesso13/5e94c9e5-cf22-4b87-af86-7ba703fd4d51
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.000213
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 10
lora_alpha: 128
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 64
lora_target_linear: true
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/G.O.D/819347714d90e9b5_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 1
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
save_steps: 50
saves_per_epoch: null
seed: 130
sequence_len: 512
special_tokens:
pad_token: <|endoftext|>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 23652205-9353-442b-a18e-09f761a8f4b3
wandb_project: 13a
wandb_run: your_name
wandb_runid: 23652205-9353-442b-a18e-09f761a8f4b3
warmup_steps: 50
weight_decay: 0.0
xformers_attention: null
5e94c9e5-cf22-4b87-af86-7ba703fd4d51
This model is a fine-tuned version of EleutherAI/pythia-410m-deduped on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8746
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.000213
- train_batch_size: 4
- eval_batch_size: 4
- seed: 130
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- training_steps: 500
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 0.0005 | 1 | 4.2553 |
3.1617 | 0.0239 | 50 | 1.5512 |
2.4236 | 0.0478 | 100 | 1.1036 |
2.8939 | 0.0717 | 150 | 1.2150 |
2.4033 | 0.0956 | 200 | 1.0835 |
2.5615 | 0.1194 | 250 | 1.1375 |
2.4282 | 0.1433 | 300 | 1.0521 |
2.3871 | 0.1672 | 350 | 0.9657 |
2.2564 | 0.1911 | 400 | 0.9130 |
2.1484 | 0.2150 | 450 | 0.8792 |
2.0612 | 0.2389 | 500 | 0.8746 |
Framework versions
- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.1