Aline Rodrigues
commited on
Commit
•
65ad224
1
Parent(s):
9bcca98
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,89 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- wer
|
| 7 |
+
model-index:
|
| 8 |
+
- name: wav2vec2-large-xlsr-mecita-coraa-portuguese-aug-random-all-03
|
| 9 |
+
results: []
|
| 10 |
+
---
|
| 11 |
+
|
| 12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 13 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 14 |
+
|
| 15 |
+
# wav2vec2-large-xlsr-mecita-coraa-portuguese-aug-random-all-03
|
| 16 |
+
|
| 17 |
+
This model is a fine-tuned version of [Edresson/wav2vec2-large-xlsr-coraa-portuguese](https://huggingface.co/Edresson/wav2vec2-large-xlsr-coraa-portuguese) on an unknown dataset.
|
| 18 |
+
It achieves the following results on the evaluation set:
|
| 19 |
+
- Loss: 0.1511
|
| 20 |
+
- Wer: 0.0808
|
| 21 |
+
- Cer: 0.0290
|
| 22 |
+
|
| 23 |
+
## Model description
|
| 24 |
+
|
| 25 |
+
More information needed
|
| 26 |
+
|
| 27 |
+
## Intended uses & limitations
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Training and evaluation data
|
| 32 |
+
|
| 33 |
+
More information needed
|
| 34 |
+
|
| 35 |
+
## Training procedure
|
| 36 |
+
|
| 37 |
+
### Training hyperparameters
|
| 38 |
+
|
| 39 |
+
The following hyperparameters were used during training:
|
| 40 |
+
- learning_rate: 3e-05
|
| 41 |
+
- train_batch_size: 16
|
| 42 |
+
- eval_batch_size: 8
|
| 43 |
+
- seed: 42
|
| 44 |
+
- gradient_accumulation_steps: 2
|
| 45 |
+
- total_train_batch_size: 32
|
| 46 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 47 |
+
- lr_scheduler_type: linear
|
| 48 |
+
- num_epochs: 100
|
| 49 |
+
- mixed_precision_training: Native AMP
|
| 50 |
+
|
| 51 |
+
### Training results
|
| 52 |
+
|
| 53 |
+
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|
| 54 |
+
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
|
| 55 |
+
| 2.883 | 1.0 | 514 | 2.5884 | 0.9955 | 0.9943 |
|
| 56 |
+
| 0.9481 | 2.0 | 1029 | 0.2560 | 0.1474 | 0.0436 |
|
| 57 |
+
| 0.742 | 3.0 | 1543 | 0.1802 | 0.1098 | 0.0340 |
|
| 58 |
+
| 0.625 | 4.0 | 2058 | 0.1590 | 0.0975 | 0.0308 |
|
| 59 |
+
| 0.6001 | 5.0 | 2572 | 0.1486 | 0.0887 | 0.0292 |
|
| 60 |
+
| 0.5208 | 6.0 | 3087 | 0.1424 | 0.0918 | 0.0284 |
|
| 61 |
+
| 0.4857 | 7.0 | 3601 | 0.1357 | 0.0844 | 0.0268 |
|
| 62 |
+
| 0.4458 | 8.0 | 4116 | 0.1375 | 0.0882 | 0.0317 |
|
| 63 |
+
| 0.4158 | 9.0 | 4630 | 0.1411 | 0.0839 | 0.0303 |
|
| 64 |
+
| 0.3915 | 10.0 | 5145 | 0.1457 | 0.0915 | 0.0319 |
|
| 65 |
+
| 0.3898 | 11.0 | 5659 | 0.1464 | 0.0870 | 0.0310 |
|
| 66 |
+
| 0.3562 | 12.0 | 6174 | 0.1500 | 0.0875 | 0.0314 |
|
| 67 |
+
| 0.3619 | 13.0 | 6688 | 0.1523 | 0.0877 | 0.0313 |
|
| 68 |
+
| 0.3283 | 14.0 | 7203 | 0.1473 | 0.0856 | 0.0290 |
|
| 69 |
+
| 0.3196 | 15.0 | 7717 | 0.1443 | 0.0844 | 0.0299 |
|
| 70 |
+
| 0.3165 | 16.0 | 8232 | 0.1413 | 0.0813 | 0.0283 |
|
| 71 |
+
| 0.2954 | 17.0 | 8746 | 0.1451 | 0.0825 | 0.0283 |
|
| 72 |
+
| 0.293 | 18.0 | 9261 | 0.1539 | 0.0822 | 0.0286 |
|
| 73 |
+
| 0.2821 | 19.0 | 9775 | 0.1552 | 0.0844 | 0.0296 |
|
| 74 |
+
| 0.2893 | 20.0 | 10290 | 0.1484 | 0.0820 | 0.0285 |
|
| 75 |
+
| 0.2609 | 21.0 | 10804 | 0.1636 | 0.0851 | 0.0307 |
|
| 76 |
+
| 0.2526 | 22.0 | 11319 | 0.1520 | 0.0856 | 0.0292 |
|
| 77 |
+
| 0.2571 | 23.0 | 11833 | 0.1449 | 0.0851 | 0.0291 |
|
| 78 |
+
| 0.2486 | 24.0 | 12348 | 0.1574 | 0.0865 | 0.0307 |
|
| 79 |
+
| 0.2501 | 25.0 | 12862 | 0.1490 | 0.0856 | 0.0295 |
|
| 80 |
+
| 0.2525 | 26.0 | 13377 | 0.1508 | 0.0827 | 0.0294 |
|
| 81 |
+
| 0.2452 | 27.0 | 13891 | 0.1511 | 0.0808 | 0.0290 |
|
| 82 |
+
|
| 83 |
+
|
| 84 |
+
### Framework versions
|
| 85 |
+
|
| 86 |
+
- Transformers 4.28.0
|
| 87 |
+
- Pytorch 2.5.0+cu121
|
| 88 |
+
- Datasets 3.1.0
|
| 89 |
+
- Tokenizers 0.13.3
|