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

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: 0.9688
- Rouge1: 38.8633
- Rouge2: 33.0802
- Rougel: 37.6956
- Rougelsum: 37.7116
- Bleu: 26.6301
- Gen Len: 11.5566
- Meteor: 0.3519
- No ans accuracy: 22.99
- Av cosine sim: 0.6861

## 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: 0.005
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|:-------:|:------:|:---------------:|:-------------:|
| 5.4434        | 1.0   | 175  | 2.1918          | 1.8449  | 1.2024  | 1.7039  | 1.7116    | 0.0     | 2.7672  | 0.0145 | 28.9700         | 0.1363        |
| 1.8436        | 1.99  | 350  | 1.1852          | 33.6062 | 26.8725 | 32.2258 | 32.241    | 20.3395 | 12.2528 | 0.2957 | 17.3800         | 0.636         |
| 1.2276        | 2.99  | 525  | 1.0630          | 33.186  | 27.4949 | 32.0715 | 32.0522   | 20.3232 | 11.0301 | 0.2957 | 21.18           | 0.6109        |
| 0.9589        | 3.98  | 700  | 1.0083          | 40.265  | 33.6652 | 38.9503 | 38.9661   | 28.0884 | 12.8545 | 0.3623 | 17.54           | 0.7157        |
| 0.7931        | 4.98  | 875  | 0.9682          | 37.9437 | 31.7611 | 36.7618 | 36.7671   | 25.7738 | 12.0286 | 0.3424 | 20.66           | 0.6825        |
| 0.6686        | 5.97  | 1050 | 0.9601          | 37.5742 | 31.9098 | 36.4225 | 36.4381   | 24.9584 | 11.4169 | 0.3398 | 22.56           | 0.6713        |
| 0.5686        | 6.97  | 1225 | 0.9620          | 43.1436 | 36.6363 | 41.7279 | 41.7571   | 32.4301 | 13.6142 | 0.3893 | 16.9400         | 0.757         |
| 0.4939        | 7.96  | 1400 | 0.9688          | 38.8633 | 33.0802 | 37.6956 | 37.7116   | 26.6301 | 11.5566 | 0.3519 | 22.99           | 0.6861        |


### Framework versions

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