---
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: mt5-small_epochs_new_new
  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_epochs_new_new

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: 1.0848
- Rouge1: 41.527
- Rouge2: 33.324
- Rougel: 38.4866
- Rougelsum: 38.4856
- Bleu: 29.906
- Gen Len: 17.1296
- Meteor: 0.377
- No ans accuracy: 47

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 9
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | No ans accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:------:|:---------------:|
| 9.0096        | 1.0   | 316  | 2.5283          | 23.4252 | 15.294  | 21.7032 | 21.7597   | 9.5703  | 12.1099 | 0.2117 | 0               |
| 3.2564        | 2.0   | 632  | 1.8337          | 33.2328 | 25.7922 | 31.2553 | 31.2709   | 15.51   | 13.8804 | 0.3108 | 0               |
| 2.5244        | 3.0   | 948  | 1.5796          | 34.1863 | 26.9908 | 32.3162 | 32.3197   | 17.5684 | 14.1904 | 0.3262 | 0               |
| 2.1686        | 3.99  | 1264 | 1.4179          | 34.565  | 27.4829 | 32.6012 | 32.6306   | 18.1896 | 14.2814 | 0.329  | 0               |
| 1.9465        | 4.99  | 1580 | 1.3050          | 41.2984 | 32.8587 | 38.3901 | 38.3985   | 28.3953 | 17.1212 | 0.3724 | 24              |
| 1.8009        | 5.99  | 1896 | 1.2428          | 41.5784 | 33.0684 | 38.6495 | 38.6555   | 28.9287 | 17.2045 | 0.3755 | 27              |
| 1.6954        | 6.99  | 2212 | 1.1992          | 40.4868 | 32.2937 | 37.6021 | 37.5986   | 28.2477 | 16.8056 | 0.3662 | 54              |
| 1.6322        | 7.99  | 2528 | 1.1769          | 37.6427 | 30.0271 | 34.8637 | 34.8951   | 26.433  | 15.5656 | 0.34   | 124             |
| 1.5845        | 8.99  | 2844 | 1.1574          | 40.3396 | 32.2547 | 37.3672 | 37.4137   | 28.6687 | 16.6457 | 0.3638 | 66              |
| 1.5425        | 9.98  | 3160 | 1.1500          | 39.1906 | 31.3426 | 36.3113 | 36.3654   | 27.8135 | 16.1679 | 0.3542 | 95              |
| 1.5137        | 10.98 | 3476 | 1.1367          | 41.4173 | 33.1848 | 38.4473 | 38.4306   | 29.6548 | 17.0306 | 0.3755 | 51              |
| 1.4826        | 11.98 | 3792 | 1.1161          | 41.4856 | 33.1913 | 38.4806 | 38.4896   | 29.5512 | 17.1031 | 0.3762 | 44              |
| 1.4514        | 12.98 | 4108 | 1.1182          | 41.8374 | 33.5091 | 38.7582 | 38.7679   | 29.8577 | 17.2987 | 0.3797 | 37              |
| 1.4444        | 13.98 | 4424 | 1.1056          | 42.0345 | 33.6905 | 38.9576 | 38.9795   | 30.1371 | 17.2669 | 0.3823 | 38              |
| 1.425         | 14.98 | 4740 | 1.0973          | 41.5086 | 33.2216 | 38.4098 | 38.4115   | 29.7019 | 17.1244 | 0.3767 | 50              |
| 1.407         | 15.97 | 5056 | 1.0890          | 41.7122 | 33.4259 | 38.605  | 38.6225   | 29.9984 | 17.1908 | 0.3794 | 44              |
| 1.4005        | 16.97 | 5372 | 1.0881          | 41.5731 | 33.2998 | 38.521  | 38.5259   | 29.9097 | 17.1027 | 0.3775 | 49              |
| 1.3865        | 17.97 | 5688 | 1.0860          | 40.9767 | 32.8412 | 37.9532 | 37.9637   | 29.4171 | 16.9404 | 0.372  | 55              |
| 1.3849        | 18.97 | 6004 | 1.0848          | 41.527  | 33.324  | 38.4866 | 38.4856   | 29.906  | 17.1296 | 0.377  | 47              |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3