| | --- |
| | license: apache-2.0 |
| | base_model: google-t5/t5-small |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - rouge |
| | model-index: |
| | - name: meeting_summarizer_model |
| | results: [] |
| | datasets: |
| | - huuuyeah/meetingbank |
| | language: |
| | - en |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # meeting_summarizer_model |
| |
|
| | This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on the dataset "huuuyeah/meetingbank". |
| | It achieves the following results on the evaluation set: |
| | - Loss: 2.3916 |
| | - Rouge1: 0.3517 |
| | - Rouge2: 0.2684 |
| | - Rougel: 0.3353 |
| | - Rougelsum: 0.3363 |
| | - Gen Len: 18.7564 |
| |
|
| | ## 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 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
| | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
| | | No log | 1.0 | 324 | 2.9030 | 0.2906 | 0.1982 | 0.2662 | 0.2663 | 18.9687 | |
| | | 5.7333 | 2.0 | 648 | 2.5094 | 0.3313 | 0.2456 | 0.3132 | 0.3138 | 18.7506 | |
| | | 5.7333 | 3.0 | 972 | 2.4188 | 0.3514 | 0.2673 | 0.3345 | 0.335 | 18.7749 | |
| | | 3.9805 | 4.0 | 1296 | 2.3916 | 0.3517 | 0.2684 | 0.3353 | 0.3363 | 18.7564 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.39.3 |
| | - Pytorch 2.2.2 |
| | - Datasets 2.18.0 |
| | - Tokenizers 0.15.2 |
