| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: qa_bm25_small_sample2 |
| | 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. --> |
| |
|
| | # qa_bm25_small_sample2 |
| | |
| | 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: 4.1438 |
| | - Rouge1: 0.1048 |
| | - Rouge2: 0.0088 |
| | - Rougel: 0.0949 |
| | - Rougelsum: 0.0949 |
| | - Gen Len: 19.0 |
| | |
| | ## 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: 1 |
| | - eval_batch_size: 1 |
| | - 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 | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | | No log | 1.0 | 108 | 12.1686 | 0.014 | 0.0 | 0.0134 | 0.0132 | 6.0357 | |
| | | No log | 2.0 | 216 | 10.8608 | 0.0122 | 0.0 | 0.0113 | 0.0113 | 6.0 | |
| | | No log | 3.0 | 324 | 8.0196 | 0.044 | 0.008 | 0.041 | 0.0407 | 9.1429 | |
| | | No log | 4.0 | 432 | 5.8188 | 0.1099 | 0.0119 | 0.0988 | 0.0983 | 19.0 | |
| | | 13.9065 | 5.0 | 540 | 4.6813 | 0.1254 | 0.0138 | 0.1104 | 0.1103 | 19.0 | |
| | | 13.9065 | 6.0 | 648 | 4.3367 | 0.1229 | 0.0158 | 0.1094 | 0.1097 | 19.0 | |
| | | 13.9065 | 7.0 | 756 | 4.2485 | 0.1172 | 0.0145 | 0.1033 | 0.1037 | 19.0 | |
| | | 13.9065 | 8.0 | 864 | 4.1780 | 0.1048 | 0.0088 | 0.0949 | 0.0949 | 19.0 | |
| | | 13.9065 | 9.0 | 972 | 4.1546 | 0.1048 | 0.0088 | 0.0949 | 0.0949 | 19.0 | |
| | | 6.0382 | 10.0 | 1080 | 4.1438 | 0.1048 | 0.0088 | 0.0949 | 0.0949 | 19.0 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.1+cu118 |
| | - Datasets 2.12.0 |
| | - Tokenizers 0.13.3 |
| | |
