RoBERTa_EmpAI_Definitivo
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9983
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: 500
- num_epochs: 13
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
No log | 1.0 | 483 | 1.0998 |
1.286 | 2.0 | 967 | 1.0487 |
1.1701 | 3.0 | 1450 | 1.0243 |
1.1044 | 4.0 | 1934 | 1.0189 |
1.0555 | 5.0 | 2417 | 1.0084 |
1.0418 | 6.0 | 2901 | 1.0030 |
1.0181 | 7.0 | 3384 | 1.0207 |
1.023 | 7.99 | 3864 | 0.9954 |
1.018 | 9.0 | 4347 | 0.9925 |
1.0144 | 10.0 | 4831 | 0.9842 |
1.0024 | 11.0 | 5314 | 0.9665 |
1.0003 | 12.0 | 5798 | 0.9864 |
0.9924 | 12.99 | 6279 | 0.9767 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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