RoBERTa-GPT2_EmpAI_FineTuned
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9871
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.3753 | 1.0 | 3867 | 4.3100 |
2.873 | 2.0 | 7734 | 2.8619 |
2.0204 | 3.0 | 11601 | 2.0694 |
1.6845 | 4.0 | 15468 | 1.7321 |
1.5994 | 5.0 | 19335 | 1.6773 |
1.3579 | 6.0 | 23202 | 1.3416 |
1.0921 | 7.0 | 27069 | 1.1302 |
0.975 | 8.0 | 30936 | 1.0375 |
0.9599 | 9.0 | 34803 | 0.9928 |
0.9228 | 10.0 | 38670 | 0.9871 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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