50pos_model
This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.4089
- Bleu: 0.0001
- Wer: 0.9459
- Rougel: 0.1326
- Gen Len: 18.9987
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: 2e-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
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Wer | Rougel | Gen Len |
---|---|---|---|---|---|---|---|
2.191 | 0.16 | 1000 | 1.3669 | 0.0001 | 0.9468 | 0.1309 | 18.999 |
1.5151 | 0.32 | 2000 | 1.2748 | 0.0001 | 0.9458 | 0.1327 | 18.9987 |
1.6193 | 0.48 | 3000 | 1.4301 | 0.0001 | 0.9457 | 0.133 | 18.9986 |
1.7458 | 0.64 | 4000 | 1.4091 | 0.0001 | 0.9459 | 0.1326 | 18.9986 |
1.7281 | 0.8 | 5000 | 1.4088 | 0.0001 | 0.9459 | 0.1326 | 18.9986 |
1.7255 | 0.96 | 6000 | 1.4089 | 0.0001 | 0.9459 | 0.1326 | 18.9986 |
1.7297 | 1.12 | 7000 | 1.4089 | 0.0001 | 0.9459 | 0.1326 | 18.9987 |
1.7197 | 1.28 | 8000 | 1.4089 | 0.0001 | 0.9459 | 0.1326 | 18.9987 |
1.7287 | 1.44 | 9000 | 1.4088 | 0.0001 | 0.9459 | 0.1326 | 18.9986 |
1.7253 | 1.6 | 10000 | 1.4088 | 0.0001 | 0.9459 | 0.1326 | 18.9987 |
1.7189 | 1.76 | 11000 | 1.4089 | 0.0001 | 0.9459 | 0.1326 | 18.9987 |
1.7257 | 1.92 | 12000 | 1.4089 | 0.0001 | 0.9459 | 0.1326 | 18.9987 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.3.0.dev20240122+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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