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parsed_csm_tool_model
This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.5103
- Rouge1: 0.0892
- Rouge2: 0.0203
- Rougel: 0.0696
- Rougelsum: 0.0684
- Gen Len: 18.375
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 37 | 4.7609 | 0.1106 | 0.017 | 0.0858 | 0.0853 | 18.75 |
| No log | 2.0 | 74 | 4.5920 | 0.083 | 0.017 | 0.0625 | 0.0613 | 18.625 |
| No log | 3.0 | 111 | 4.5263 | 0.0891 | 0.0203 | 0.0641 | 0.0632 | 18.625 |
| No log | 4.0 | 148 | 4.5103 | 0.0892 | 0.0203 | 0.0696 | 0.0684 | 18.375 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
