File size: 4,025 Bytes
ec525ac c6b8eb2 ec525ac c6b8eb2 ec525ac |
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 92 93 94 |
---
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: es_fi_all_quy
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. -->
# es_fi_all_quy
This model is a fine-tuned version of [nouman-10/es_fi_all_quy](https://huggingface.co/nouman-10/es_fi_all_quy) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4691
- Bleu: 1.3097
- Chrf: 33.573
- Gen Len: 42.0221
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Chrf | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:-------:|
| 0.2653 | 0.09 | 1000 | 0.4870 | 1.3376 | 32.1158 | 43.001 |
| 0.2668 | 0.17 | 2000 | 0.4826 | 1.3753 | 32.002 | 46.505 |
| 0.2567 | 0.26 | 3000 | 0.4820 | 1.2717 | 31.9404 | 46.7274 |
| 0.2561 | 0.34 | 4000 | 0.4825 | 1.4256 | 32.4758 | 41.7274 |
| 0.2618 | 0.43 | 5000 | 0.4850 | 1.6935 | 33.2306 | 37.2012 |
| 0.2705 | 0.51 | 6000 | 0.4723 | 1.372 | 32.4431 | 46.84 |
| 0.2681 | 0.6 | 7000 | 0.4758 | 1.4419 | 32.8507 | 45.6016 |
| 0.2629 | 0.68 | 8000 | 0.4737 | 1.4636 | 33.3288 | 40.0382 |
| 0.2773 | 0.77 | 9000 | 0.4715 | 1.2296 | 33.1241 | 41.502 |
| 0.2702 | 0.85 | 10000 | 0.4663 | 1.2579 | 32.8273 | 44.9034 |
| 0.2683 | 0.94 | 11000 | 0.4694 | 1.6207 | 32.8479 | 42.3964 |
| 0.259 | 1.02 | 12000 | 0.4766 | 1.4934 | 32.6413 | 41.0815 |
| 0.2537 | 1.11 | 13000 | 0.4713 | 1.7586 | 33.3814 | 39.9638 |
| 0.2516 | 1.19 | 14000 | 0.4724 | 1.593 | 33.4105 | 41.832 |
| 0.2574 | 1.28 | 15000 | 0.4749 | 1.3373 | 33.3664 | 42.3662 |
| 0.2523 | 1.37 | 16000 | 0.4701 | 1.1924 | 32.6157 | 42.7706 |
| 0.2462 | 1.45 | 17000 | 0.4710 | 1.5688 | 33.5992 | 40.5282 |
| 0.2513 | 1.54 | 18000 | 0.4723 | 1.2722 | 32.1578 | 47.4225 |
| 0.2504 | 1.62 | 19000 | 0.4728 | 1.3897 | 32.6709 | 40.8893 |
| 0.2502 | 1.71 | 20000 | 0.4714 | 1.5999 | 33.6673 | 41.5362 |
| 0.2434 | 1.79 | 21000 | 0.4715 | 1.9393 | 33.6971 | 40.8944 |
| 0.2483 | 1.88 | 22000 | 0.4688 | 1.8308 | 34.1117 | 37.7565 |
| 0.2435 | 1.96 | 23000 | 0.4693 | 1.8643 | 34.5409 | 38.6237 |
| 0.2377 | 2.05 | 24000 | 0.4702 | 1.6217 | 33.6401 | 40.4779 |
| 0.235 | 2.13 | 25000 | 0.4707 | 1.5441 | 33.588 | 39.8974 |
| 0.2345 | 2.22 | 26000 | 0.4710 | 2.0248 | 33.7469 | 37.2535 |
| 0.2423 | 2.3 | 27000 | 0.4691 | 1.9699 | 33.4757 | 37.9889 |
| 0.2388 | 2.39 | 28000 | 0.4669 | 1.5651 | 33.1965 | 39.7646 |
| 0.2367 | 2.47 | 29000 | 0.4682 | 1.69 | 33.9955 | 38.3199 |
| 0.2392 | 2.56 | 30000 | 0.4720 | 1.9972 | 33.902 | 41.2525 |
| 0.2382 | 2.65 | 31000 | 0.4721 | 2.0682 | 33.6693 | 38.3833 |
| 0.2373 | 2.73 | 32000 | 0.4690 | 2.0952 | 33.553 | 38.3229 |
| 0.2356 | 2.82 | 33000 | 0.4691 | 1.3097 | 33.573 | 42.0221 |
### Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
|