---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: qa_bm25_small_sample2
  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. -->

# qa_bm25_small_sample2

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: 4.1438
- Rouge1: 0.1048
- Rouge2: 0.0088
- Rougel: 0.0949
- Rougelsum: 0.0949
- Gen Len: 19.0

## 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 108  | 12.1686         | 0.014  | 0.0    | 0.0134 | 0.0132    | 6.0357  |
| No log        | 2.0   | 216  | 10.8608         | 0.0122 | 0.0    | 0.0113 | 0.0113    | 6.0     |
| No log        | 3.0   | 324  | 8.0196          | 0.044  | 0.008  | 0.041  | 0.0407    | 9.1429  |
| No log        | 4.0   | 432  | 5.8188          | 0.1099 | 0.0119 | 0.0988 | 0.0983    | 19.0    |
| 13.9065       | 5.0   | 540  | 4.6813          | 0.1254 | 0.0138 | 0.1104 | 0.1103    | 19.0    |
| 13.9065       | 6.0   | 648  | 4.3367          | 0.1229 | 0.0158 | 0.1094 | 0.1097    | 19.0    |
| 13.9065       | 7.0   | 756  | 4.2485          | 0.1172 | 0.0145 | 0.1033 | 0.1037    | 19.0    |
| 13.9065       | 8.0   | 864  | 4.1780          | 0.1048 | 0.0088 | 0.0949 | 0.0949    | 19.0    |
| 13.9065       | 9.0   | 972  | 4.1546          | 0.1048 | 0.0088 | 0.0949 | 0.0949    | 19.0    |
| 6.0382        | 10.0  | 1080 | 4.1438          | 0.1048 | 0.0088 | 0.0949 | 0.0949    | 19.0    |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3