EN_mt5-small_10_spider
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4350
- Rouge2 Precision: 0.3068
- Rouge2 Recall: 0.202
- Rouge2 Fmeasure: 0.2177
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: 5e-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: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
No log | 1.0 | 438 | 4.5527 | 0.0024 | 0.001 | 0.0014 |
17.6146 | 2.0 | 876 | 1.6584 | 0.0 | 0.0 | 0.0 |
2.53 | 3.0 | 1314 | 1.5698 | 0.0 | 0.0 | 0.0 |
1.9045 | 4.0 | 1752 | 1.3153 | 0.0206 | 0.0074 | 0.0106 |
1.5088 | 5.0 | 2190 | 0.6748 | 0.1009 | 0.056 | 0.0623 |
0.8005 | 6.0 | 2628 | 0.5124 | 0.2301 | 0.1513 | 0.1593 |
0.5297 | 7.0 | 3066 | 0.4683 | 0.2899 | 0.1903 | 0.2021 |
0.4507 | 8.0 | 3504 | 0.4464 | 0.2966 | 0.2016 | 0.2129 |
0.4507 | 9.0 | 3942 | 0.4385 | 0.3125 | 0.2065 | 0.2224 |
0.4161 | 10.0 | 4380 | 0.4350 | 0.3068 | 0.202 | 0.2177 |
Framework versions
- Transformers 4.26.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.7.dev0
- Tokenizers 0.13.3
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