| | --- |
| | license: apache-2.0 |
| | base_model: google/mt5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | - bleu |
| | model-index: |
| | - name: mt5-small_test_35 |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # mt5-small_test_35 |
| |
|
| | This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7383 |
| | - Rouge1: 43.9482 |
| | - Rouge2: 38.4156 |
| | - Rougel: 42.6232 |
| | - Rougelsum: 42.674 |
| | - Bleu: 33.3469 |
| | - Gen Len: 12.4725 |
| | - Meteor: 0.4016 |
| | - True negatives: 70.997 |
| | - False negatives: 11.8271 |
| | - Cosine Sim: 0.7532 |
| |
|
| | ## 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: 0.001 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 16 |
| | - seed: 9 |
| | - gradient_accumulation_steps: 8 |
| | - total_train_batch_size: 128 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 20 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Gen Len | Meteor | True negatives | False negatives | Cosine Sim | |
| | |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:------:|:--------------:|:---------------:|:----------:| |
| | | 2.4524 | 1.0 | 175 | 0.9783 | 17.6419 | 14.587 | 17.1176 | 17.1329 | 6.1296 | 7.3271 | 0.1531 | 75.7704 | 59.8602 | 0.3786 | |
| | | 1.1433 | 1.99 | 350 | 0.8448 | 38.9957 | 33.2414 | 37.7868 | 37.8653 | 27.5883 | 12.3274 | 0.3526 | 60.3625 | 17.236 | 0.6954 | |
| | | 0.9381 | 2.99 | 525 | 0.8067 | 42.4146 | 36.3126 | 40.964 | 41.0427 | 31.5838 | 13.0716 | 0.3833 | 59.6375 | 11.1801 | 0.7425 | |
| | | 0.8116 | 3.98 | 700 | 0.7712 | 43.8741 | 37.8446 | 42.3785 | 42.4778 | 33.1873 | 13.0574 | 0.3982 | 61.9335 | 9.5238 | 0.7586 | |
| | | 0.7218 | 4.98 | 875 | 0.7439 | 43.1579 | 37.3057 | 41.7059 | 41.8024 | 32.5124 | 12.7853 | 0.3931 | 65.8006 | 11.2836 | 0.7498 | |
| | | 0.6461 | 5.97 | 1050 | 0.7254 | 39.9226 | 34.552 | 38.7033 | 38.7665 | 27.9936 | 11.4675 | 0.3638 | 77.9456 | 18.5041 | 0.7003 | |
| | | 0.5852 | 6.97 | 1225 | 0.7290 | 44.131 | 38.3527 | 42.7974 | 42.8549 | 33.6955 | 12.7811 | 0.4026 | 67.855 | 10.3778 | 0.7599 | |
| | | 0.5421 | 7.96 | 1400 | 0.7248 | 44.5368 | 38.7443 | 43.2111 | 43.2976 | 34.1121 | 12.7875 | 0.4071 | 67.5529 | 10.4037 | 0.7637 | |
| | | 0.5026 | 8.96 | 1575 | 0.7383 | 43.9482 | 38.4156 | 42.6232 | 42.674 | 33.3469 | 12.4725 | 0.4016 | 70.997 | 11.8271 | 0.7532 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.31.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
| | |
