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-archeologie
  results:
  - task:
      name: Summarization
      type: summarization
    metrics:
    - name: Rouge1
      type: rouge
      value: 37.1845
---

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# barthez-deft-archeologie

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: 2.0733
- Rouge1: 37.1845
- Rouge2: 16.9534
- Rougel: 28.8416
- Rougelsum: 29.077
- Gen Len: 34.4028

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.4832        | 1.0   | 108  | 2.4237          | 22.6662 | 10.009  | 19.8729 | 19.8814   | 15.8333 |
| 2.557         | 2.0   | 216  | 2.2328          | 24.8102 | 11.9911 | 20.4773 | 20.696    | 19.0139 |
| 2.2702        | 3.0   | 324  | 2.2002          | 25.6482 | 11.6191 | 21.8383 | 21.9341   | 18.1944 |
| 2.1119        | 4.0   | 432  | 2.1266          | 25.5806 | 11.9765 | 21.3973 | 21.3503   | 19.4306 |
| 1.9582        | 5.0   | 540  | 2.1072          | 25.6578 | 12.2709 | 22.182  | 22.0548   | 19.1528 |
| 1.8137        | 6.0   | 648  | 2.1008          | 26.5272 | 11.4033 | 22.359  | 22.3259   | 19.4722 |
| 1.7725        | 7.0   | 756  | 2.1074          | 25.0405 | 11.1773 | 21.1369 | 21.1847   | 19.1806 |
| 1.6772        | 8.0   | 864  | 2.0959          | 26.5237 | 11.6028 | 22.5018 | 22.3931   | 19.3333 |
| 1.5798        | 9.0   | 972  | 2.0976          | 27.7443 | 11.9898 | 22.4052 | 22.2954   | 19.7222 |
| 1.4753        | 10.0  | 1080 | 2.0733          | 28.3502 | 12.9162 | 22.6352 | 22.6015   | 19.8194 |
| 1.4646        | 11.0  | 1188 | 2.1091          | 27.9198 | 12.8591 | 23.0718 | 23.0779   | 19.6111 |
| 1.4082        | 12.0  | 1296 | 2.1036          | 28.8509 | 13.0987 | 23.4189 | 23.5044   | 19.4861 |
| 1.2862        | 13.0  | 1404 | 2.1222          | 28.6641 | 12.8157 | 22.6799 | 22.7051   | 19.8611 |
| 1.2612        | 14.0  | 1512 | 2.1487          | 26.9709 | 11.6084 | 22.0312 | 22.0543   | 19.875  |
| 1.2327        | 15.0  | 1620 | 2.1808          | 28.218  | 12.6239 | 22.7372 | 22.7881   | 19.7361 |
| 1.2264        | 16.0  | 1728 | 2.1778          | 26.7393 | 11.4474 | 21.6057 | 21.555    | 19.7639 |
| 1.1848        | 17.0  | 1836 | 2.1995          | 27.6902 | 12.1082 | 22.0406 | 22.0101   | 19.6806 |
| 1.133         | 18.0  | 1944 | 2.2038          | 27.0402 | 12.1846 | 21.7793 | 21.7513   | 19.8056 |
| 1.168         | 19.0  | 2052 | 2.2116          | 27.5149 | 11.9876 | 22.1113 | 22.1527   | 19.7222 |
| 1.1206        | 20.0  | 2160 | 2.2133          | 28.2321 | 12.677  | 22.749  | 22.8485   | 19.5972 |


### Framework versions

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