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

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: 0.7428
- Rouge1: 43.12
- Rouge2: 37.6639
- Rougel: 41.8367
- Rougelsum: 41.904
- Bleu: 31.957
- Gen Len: 12.1285
- Meteor: 0.3936
- No ans accuracy: 22.29
- Av cosine sim: 0.7406

## 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 | No ans accuracy | Av cosine sim |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:------:|:---------------:|:-------------:|
| 3.1455        | 1.0   | 175  | 0.9832          | 18.7107 | 15.4897 | 18.1977 | 18.2212   | 7.0634  | 7.6229  | 0.1626 | 22.4000         | 0.3949        |
| 1.1623        | 1.99  | 350  | 0.8542          | 38.7675 | 32.704  | 37.3557 | 37.3949   | 27.4323 | 12.5135 | 0.3487 | 17.9900         | 0.6992        |
| 0.9431        | 2.99  | 525  | 0.8017          | 41.6216 | 35.6002 | 40.2386 | 40.2881   | 30.7994 | 12.8117 | 0.3755 | 18.37           | 0.7304        |
| 0.8119        | 3.98  | 700  | 0.7787          | 43.5805 | 37.4117 | 42.1059 | 42.155    | 32.9646 | 13.2176 | 0.3947 | 17.7400         | 0.7582        |
| 0.7235        | 4.98  | 875  | 0.7477          | 43.4124 | 37.2017 | 41.8468 | 41.9097   | 32.9345 | 13.116  | 0.3946 | 18.92           | 0.7561        |
| 0.6493        | 5.97  | 1050 | 0.7266          | 40.4764 | 34.9927 | 39.0999 | 39.1711   | 29.0601 | 11.748  | 0.3687 | 22.6500         | 0.7071        |
| 0.5871        | 6.97  | 1225 | 0.7284          | 43.3812 | 37.5544 | 42.0405 | 42.0865   | 32.8345 | 12.6063 | 0.3949 | 21.05           | 0.7485        |
| 0.5453        | 7.96  | 1400 | 0.7389          | 43.4549 | 37.76   | 42.1025 | 42.215    | 32.6726 | 12.4537 | 0.3965 | 21.44           | 0.7496        |
| 0.5038        | 8.96  | 1575 | 0.7428          | 43.12   | 37.6639 | 41.8367 | 41.904    | 31.957  | 12.1285 | 0.3936 | 22.29           | 0.7406        |


### Framework versions

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