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

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: 0.7284
- Rouge1: 43.3718
- Rouge2: 37.5973
- Rougel: 42.0502
- Rougelsum: 42.0648
- Bleu: 32.8345
- Gen Len: 12.6063
- Meteor: 0.3949
- True negatives: 70.2115
- False negatives: 11.206
- Cosine Sim: 0.7485

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:------:|:--------------:|:---------------:|:----------:|
| 3.1455        | 1.0   | 175  | 0.9832          | 18.7269 | 15.517  | 18.22   | 18.223    | 7.0634  | 7.6229  | 0.1626 | 74.6828        | 57.1687         | 0.3949     |
| 1.1623        | 1.99  | 350  | 0.8542          | 38.7603 | 32.7237 | 37.3447 | 37.3752   | 27.4323 | 12.5135 | 0.3487 | 60.0           | 15.942          | 0.6992     |
| 0.9431        | 2.99  | 525  | 0.8017          | 41.5759 | 35.6108 | 40.2536 | 40.2695   | 30.7994 | 12.8117 | 0.3755 | 61.2689        | 12.3447         | 0.7304     |
| 0.8119        | 3.98  | 700  | 0.7787          | 43.5881 | 37.4245 | 42.1096 | 42.1248   | 32.9646 | 13.2176 | 0.3947 | 59.1541        | 9.5238          | 0.7582     |
| 0.7235        | 4.98  | 875  | 0.7477          | 43.4069 | 37.2246 | 41.8444 | 41.8616   | 32.9345 | 13.116  | 0.3946 | 63.0816        | 9.8085          | 0.7561     |
| 0.6493        | 5.97  | 1050 | 0.7266          | 40.4506 | 35.0072 | 39.1206 | 39.1181   | 29.0601 | 11.748  | 0.3687 | 75.5287        | 17.2101         | 0.7071     |
| 0.5871        | 6.97  | 1225 | 0.7284          | 43.3718 | 37.5973 | 42.0502 | 42.0648   | 32.8345 | 12.6063 | 0.3949 | 70.2115        | 11.206          | 0.7485     |


### Framework versions

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