---
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