pytorch mbart text2text-generation transformers generated_from_trainer license:apache-2.0 model-index autotrain_compatible
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: barthez-deft-chimie
  results:
  - task:
      name: Summarization
      type: summarization
    metrics:
    - name: Rouge1
      type: rouge
      value: 31.8947
---

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# barthez-deft-chimie

This model is a fine-tuned version of [moussaKam/barthez](https://huggingface.co/moussaKam/barthez) on an unknown dataset.

**Note**: this model is one of the preliminary experiments and it underperforms the models published in the paper (using [MBartHez](https://huggingface.co/moussaKam/mbarthez) and HAL/Wiki pre-training + copy mechanisms)

It achieves the following results on the evaluation set:
- Loss: 2.0710
- Rouge1: 31.8947
- Rouge2: 16.7563
- Rougel: 23.5428
- Rougelsum: 23.4918
- Gen Len: 38.5256


 
## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.8022        | 1.0   | 118  | 2.5491          | 16.8208 | 7.0027  | 13.957  | 14.0479   | 19.1538 |
| 2.9286        | 2.0   | 236  | 2.3074          | 17.5356 | 7.8717  | 14.4874 | 14.5044   | 19.9487 |
| 2.5422        | 3.0   | 354  | 2.2322          | 19.6491 | 9.4156  | 15.9467 | 15.9433   | 19.7051 |
| 2.398         | 4.0   | 472  | 2.1500          | 18.7166 | 9.859   | 15.7535 | 15.8036   | 19.9231 |
| 2.2044        | 5.0   | 590  | 2.1372          | 19.978  | 10.6235 | 16.1348 | 16.1274   | 19.6154 |
| 1.9405        | 6.0   | 708  | 2.0992          | 20.226  | 10.551  | 16.6928 | 16.7211   | 19.9744 |
| 1.8544        | 7.0   | 826  | 2.0841          | 19.8869 | 10.8456 | 16.1072 | 16.097    | 19.8846 |
| 1.7536        | 8.0   | 944  | 2.0791          | 19.3017 | 9.4921  | 16.1541 | 16.2167   | 19.859  |
| 1.6914        | 9.0   | 1062 | 2.0710          | 21.3848 | 10.4088 | 17.1963 | 17.2254   | 19.8846 |
| 1.654         | 10.0  | 1180 | 2.1069          | 22.3811 | 10.7987 | 18.7595 | 18.761    | 19.9231 |
| 1.5899        | 11.0  | 1298 | 2.0919          | 20.8546 | 10.6958 | 16.8637 | 16.9499   | 19.8077 |
| 1.4661        | 12.0  | 1416 | 2.1065          | 22.3677 | 11.7472 | 18.262  | 18.3      | 19.9744 |
| 1.4205        | 13.0  | 1534 | 2.1164          | 20.5845 | 10.7825 | 16.9972 | 17.0216   | 19.9359 |
| 1.3797        | 14.0  | 1652 | 2.1240          | 22.2561 | 11.303  | 17.5064 | 17.5815   | 19.9744 |
| 1.3724        | 15.0  | 1770 | 2.1187          | 23.2825 | 11.912  | 18.5208 | 18.5499   | 19.9359 |
| 1.3404        | 16.0  | 1888 | 2.1394          | 22.1305 | 10.5258 | 17.772  | 17.8202   | 19.9744 |
| 1.2846        | 17.0  | 2006 | 2.1502          | 21.567  | 11.0557 | 17.2562 | 17.2974   | 20.0    |
| 1.2871        | 18.0  | 2124 | 2.1572          | 22.5871 | 11.702  | 18.2906 | 18.3826   | 19.9744 |
| 1.2422        | 19.0  | 2242 | 2.1613          | 23.0935 | 11.6824 | 18.6087 | 18.6777   | 19.9744 |
| 1.2336        | 20.0  | 2360 | 2.1581          | 22.6789 | 11.4363 | 18.1661 | 18.2346   | 19.9487 |


### Framework versions

- Transformers 4.10.2
- Pytorch 1.7.1+cu110
- Datasets 1.11.0
- Tokenizers 0.10.3
