metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: roberta-base_auditor_sentiment
results: []
roberta-base_auditor_sentiment
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5356
- Accuracy: 0.8554
- Precision: 0.8224
- Recall: 0.8722
- F1: 0.8414
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4217 | 1.0 | 485 | 0.6358 | 0.8223 | 0.8142 | 0.8135 | 0.8134 |
| 0.6538 | 2.0 | 970 | 0.6491 | 0.8388 | 0.8584 | 0.8025 | 0.8192 |
| 0.3961 | 3.0 | 1455 | 0.5356 | 0.8554 | 0.8224 | 0.8722 | 0.8414 |
| 0.1121 | 4.0 | 1940 | 0.7393 | 0.8512 | 0.8414 | 0.8477 | 0.8428 |
| 0.0192 | 5.0 | 2425 | 0.7233 | 0.8698 | 0.8581 | 0.8743 | 0.8657 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1