metadata
license: mit
base_model: gpt2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: SentimentT2_GPT2
results: []
SentimentT2_GPT2
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9470
- Accuracy: 0.8644
- F1: 0.8728
- Auc Roc: 0.9185
- Log Loss: 0.9470
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Auc Roc | Log Loss |
|---|---|---|---|---|---|---|---|
| 1.0534 | 1.0 | 1618 | 0.6479 | 0.8694 | 0.8696 | 0.9298 | 0.6479 |
| 0.6971 | 2.0 | 3236 | 1.0859 | 0.8371 | 0.8581 | 0.9236 | 1.0859 |
| 0.5832 | 3.0 | 4854 | 0.9261 | 0.8495 | 0.8672 | 0.9255 | 0.9261 |
| 0.4402 | 4.0 | 6472 | 0.8507 | 0.8719 | 0.8804 | 0.9251 | 0.8507 |
| 0.3475 | 5.0 | 8090 | 0.9284 | 0.8657 | 0.8735 | 0.9198 | 0.9283 |
| 0.2985 | 6.0 | 9708 | 0.9470 | 0.8644 | 0.8728 | 0.9185 | 0.9470 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1