File size: 3,533 Bytes
45a76a7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 |
---
license: cc-by-nc-4.0
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: NNLB-alt-en-bleu-ht
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. -->
# NNLB-alt-en-bleu-ht
This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4011
- Bleu: 40.828
- Gen Len: 26.385
## 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: 0.0001
- train_batch_size: 14
- eval_batch_size: 14
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 2.0036 | 1.0 | 799 | 1.4377 | 25.1487 | 25.036 |
| 1.2584 | 2.0 | 1598 | 1.3276 | 29.603 | 25.723 |
| 1.0147 | 3.0 | 2397 | 1.3204 | 31.3967 | 25.776 |
| 0.7379 | 4.0 | 3196 | 1.3678 | 32.4951 | 25.266 |
| 0.6228 | 5.0 | 3995 | 1.4250 | 34.6087 | 26.083 |
| 0.4327 | 6.0 | 4794 | 1.5342 | 36.6073 | 26.174 |
| 0.3437 | 7.0 | 5593 | 1.5952 | 37.7791 | 26.265 |
| 0.2689 | 8.0 | 6392 | 1.6993 | 38.16 | 26.376 |
| 0.2029 | 9.0 | 7191 | 1.7994 | 39.433 | 26.766 |
| 0.1711 | 10.0 | 7990 | 1.8893 | 39.2816 | 26.574 |
| 0.1214 | 11.0 | 8789 | 1.9661 | 39.5599 | 26.687 |
| 0.1017 | 12.0 | 9588 | 1.9928 | 39.7801 | 26.845 |
| 0.0855 | 13.0 | 10387 | 2.0508 | 39.8043 | 26.641 |
| 0.0679 | 14.0 | 11186 | 2.0998 | 40.3389 | 26.526 |
| 0.06 | 15.0 | 11985 | 2.1350 | 40.0964 | 26.395 |
| 0.0475 | 16.0 | 12784 | 2.1676 | 40.1536 | 26.614 |
| 0.0407 | 17.0 | 13583 | 2.2040 | 40.298 | 26.494 |
| 0.0347 | 18.0 | 14382 | 2.2294 | 40.5207 | 26.612 |
| 0.0315 | 19.0 | 15181 | 2.2484 | 40.3323 | 26.53 |
| 0.0286 | 20.0 | 15980 | 2.2828 | 40.3167 | 26.718 |
| 0.0241 | 21.0 | 16779 | 2.3015 | 40.0766 | 26.306 |
| 0.0213 | 22.0 | 17578 | 2.3267 | 40.477 | 26.457 |
| 0.0183 | 23.0 | 18377 | 2.3410 | 40.4013 | 26.406 |
| 0.0164 | 24.0 | 19176 | 2.3457 | 40.3643 | 26.534 |
| 0.0157 | 25.0 | 19975 | 2.3533 | 40.3967 | 26.506 |
| 0.0133 | 26.0 | 20774 | 2.3734 | 40.7786 | 26.38 |
| 0.0119 | 27.0 | 21573 | 2.3750 | 40.8653 | 26.525 |
| 0.0106 | 28.0 | 22372 | 2.3896 | 40.8371 | 26.503 |
| 0.0095 | 29.0 | 23171 | 2.3893 | 40.831 | 26.398 |
| 0.0094 | 30.0 | 23970 | 2.4011 | 40.828 | 26.385 |
### Framework versions
- Transformers 4.21.0
- Pytorch 1.10.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
|