metadata
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
barthez-deft-chimie
This model is a fine-tuned version of 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 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