|
|
--- |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
datasets: |
|
|
- ccmatrix |
|
|
metrics: |
|
|
- bleu |
|
|
model-index: |
|
|
- name: t5-base_fr-finetuned-en-to-it |
|
|
results: |
|
|
- task: |
|
|
name: Sequence-to-sequence Language Modeling |
|
|
type: text2text-generation |
|
|
dataset: |
|
|
name: ccmatrix |
|
|
type: ccmatrix |
|
|
config: en-it |
|
|
split: train[3000:12000] |
|
|
args: en-it |
|
|
metrics: |
|
|
- name: Bleu |
|
|
type: bleu |
|
|
value: 20.3152 |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# t5-base_fr-finetuned-en-to-it |
|
|
|
|
|
This model is a fine-tuned version of [j0hngou/t5-base-finetuned-en-to-fr](https://huggingface.co/j0hngou/t5-base-finetuned-en-to-fr) on the ccmatrix dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 1.4677 |
|
|
- Bleu: 20.3152 |
|
|
- Gen Len: 51.4433 |
|
|
|
|
|
## 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: 32 |
|
|
- eval_batch_size: 32 |
|
|
- seed: 42 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 40 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
|
|
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
|
|
| No log | 1.0 | 282 | 2.0344 | 6.8826 | 64.574 | |
|
|
| 2.3997 | 2.0 | 564 | 1.9371 | 7.9377 | 64.274 | |
|
|
| 2.3997 | 3.0 | 846 | 1.8740 | 9.2364 | 59.8673 | |
|
|
| 2.145 | 4.0 | 1128 | 1.8240 | 9.8068 | 60.566 | |
|
|
| 2.145 | 5.0 | 1410 | 1.7813 | 10.3961 | 60.106 | |
|
|
| 2.0183 | 6.0 | 1692 | 1.7476 | 11.2005 | 59.032 | |
|
|
| 2.0183 | 7.0 | 1974 | 1.7152 | 11.8127 | 58.1673 | |
|
|
| 1.9185 | 8.0 | 2256 | 1.6872 | 12.4843 | 57.5787 | |
|
|
| 1.8414 | 9.0 | 2538 | 1.6643 | 13.4338 | 55.502 | |
|
|
| 1.8414 | 10.0 | 2820 | 1.6459 | 13.7847 | 55.6753 | |
|
|
| 1.7755 | 11.0 | 3102 | 1.6273 | 14.6959 | 53.838 | |
|
|
| 1.7755 | 12.0 | 3384 | 1.6121 | 15.2948 | 53.4127 | |
|
|
| 1.7224 | 13.0 | 3666 | 1.5967 | 15.878 | 53.0733 | |
|
|
| 1.7224 | 14.0 | 3948 | 1.5809 | 16.3788 | 52.778 | |
|
|
| 1.6751 | 15.0 | 4230 | 1.5689 | 16.7415 | 52.8 | |
|
|
| 1.6358 | 16.0 | 4512 | 1.5580 | 17.0318 | 52.854 | |
|
|
| 1.6358 | 17.0 | 4794 | 1.5509 | 17.6302 | 52.0947 | |
|
|
| 1.5921 | 18.0 | 5076 | 1.5389 | 17.4239 | 52.71 | |
|
|
| 1.5921 | 19.0 | 5358 | 1.5317 | 17.9003 | 52.3427 | |
|
|
| 1.5696 | 20.0 | 5640 | 1.5253 | 17.769 | 52.928 | |
|
|
| 1.5696 | 21.0 | 5922 | 1.5172 | 18.2974 | 51.8173 | |
|
|
| 1.5344 | 22.0 | 6204 | 1.5117 | 18.5755 | 52.012 | |
|
|
| 1.5344 | 23.0 | 6486 | 1.5046 | 18.5362 | 52.1447 | |
|
|
| 1.5136 | 24.0 | 6768 | 1.5034 | 18.7394 | 51.9887 | |
|
|
| 1.4968 | 25.0 | 7050 | 1.4968 | 19.1622 | 51.736 | |
|
|
| 1.4968 | 26.0 | 7332 | 1.4947 | 19.1636 | 51.8467 | |
|
|
| 1.472 | 27.0 | 7614 | 1.4886 | 19.3845 | 51.774 | |
|
|
| 1.472 | 28.0 | 7896 | 1.4844 | 19.5481 | 51.458 | |
|
|
| 1.4575 | 29.0 | 8178 | 1.4827 | 19.739 | 51.4593 | |
|
|
| 1.4575 | 30.0 | 8460 | 1.4791 | 19.818 | 51.62 | |
|
|
| 1.4435 | 31.0 | 8742 | 1.4763 | 19.904 | 51.5167 | |
|
|
| 1.4336 | 32.0 | 9024 | 1.4750 | 19.9507 | 51.3787 | |
|
|
| 1.4336 | 33.0 | 9306 | 1.4742 | 20.0704 | 51.3527 | |
|
|
| 1.4236 | 34.0 | 9588 | 1.4717 | 20.2553 | 51.1967 | |
|
|
| 1.4236 | 35.0 | 9870 | 1.4705 | 20.3014 | 51.156 | |
|
|
| 1.4188 | 36.0 | 10152 | 1.4697 | 20.2263 | 51.4173 | |
|
|
| 1.4188 | 37.0 | 10434 | 1.4687 | 20.244 | 51.394 | |
|
|
| 1.412 | 38.0 | 10716 | 1.4681 | 20.2699 | 51.5993 | |
|
|
| 1.412 | 39.0 | 10998 | 1.4676 | 20.2758 | 51.4473 | |
|
|
| 1.4087 | 40.0 | 11280 | 1.4677 | 20.3152 | 51.4433 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.22.1 |
|
|
- Pytorch 1.12.1 |
|
|
- Datasets 2.5.1 |
|
|
- Tokenizers 0.11.0 |
|
|
|
