fine_tuned_t5_small_model-naive-approach
This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.3579
- Rouge1: 0.3553
- Rouge2: 0.1154
- Rougel: 0.2155
- Rougelsum: 0.2154
- Gen Len: 130.1211
- Bert F1: 0.8401
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: 15
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | Bert F1 |
|---|---|---|---|---|---|---|---|---|---|
| 4.3358 | 2.1053 | 200 | 3.5813 | 0.3207 | 0.1049 | 0.1965 | 0.1964 | 112.5737 | 0.8379 |
| 3.6728 | 4.2105 | 400 | 3.4776 | 0.3307 | 0.1098 | 0.2012 | 0.2007 | 120.2947 | 0.8382 |
| 3.5819 | 6.3158 | 600 | 3.4250 | 0.3422 | 0.114 | 0.2086 | 0.2084 | 122.5947 | 0.8399 |
| 3.5355 | 8.4211 | 800 | 3.3926 | 0.345 | 0.1142 | 0.2106 | 0.2106 | 125.2474 | 0.8398 |
| 3.5078 | 10.5263 | 1000 | 3.3709 | 0.3475 | 0.113 | 0.2118 | 0.2117 | 128.4211 | 0.8386 |
| 3.4899 | 12.6316 | 1200 | 3.3615 | 0.3538 | 0.1145 | 0.2157 | 0.2155 | 130.8632 | 0.8396 |
| 3.4672 | 14.7368 | 1400 | 3.3579 | 0.3553 | 0.1154 | 0.2155 | 0.2154 | 130.1211 | 0.8401 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0