File size: 3,560 Bytes
295366e 012a3bc 295366e b624a0f 295366e b624a0f 295366e b624a0f 295366e 409d21e 012a3bc 295366e 409d21e 295366e 012a3bc 295366e b624a0f 295366e b624a0f 012a3bc 02248bd |
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 |
---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-Arabic-phoneme
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. -->
# wav2vec2-large-xls-r-300m-Arabic-phoneme
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0335
- Per: 0.0199
- Wer: 0.0225
## 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: 0.0005
- train_batch_size: 8
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- num_epochs: 30.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Per | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 5.3718 | 1.0 | 102 | 2.1140 | 1.0 | 1.0 |
| 2.036 | 2.0 | 204 | 2.0637 | 1.0 | 1.0 |
| 2.0175 | 3.0 | 306 | 2.1252 | 1.0 | 1.0 |
| 1.9463 | 4.0 | 408 | 1.7014 | 0.9942 | 0.9887 |
| 1.702 | 5.0 | 510 | 1.7257 | 0.9944 | 0.9892 |
| 1.6475 | 6.0 | 612 | 1.5855 | 0.9897 | 0.9798 |
| 1.4766 | 7.0 | 714 | 1.2777 | 0.9787 | 0.9641 |
| 1.0363 | 8.0 | 816 | 0.7926 | 0.7738 | 0.7731 |
| 0.5964 | 9.0 | 918 | 0.4220 | 0.3994 | 0.4133 |
| 0.3437 | 10.0 | 1020 | 0.2307 | 0.1387 | 0.1549 |
| 0.2052 | 11.0 | 1122 | 0.1587 | 0.0645 | 0.0738 |
| 0.1509 | 12.0 | 1224 | 0.1314 | 0.0464 | 0.0544 |
| 0.1256 | 13.0 | 1326 | 0.1070 | 0.0448 | 0.0518 |
| 0.0935 | 14.0 | 1428 | 0.0854 | 0.0394 | 0.0452 |
| 0.0779 | 15.0 | 1530 | 0.0896 | 0.0376 | 0.0440 |
| 0.0674 | 16.0 | 1632 | 0.0625 | 0.0255 | 0.0306 |
| 0.0558 | 17.0 | 1734 | 0.0573 | 0.0270 | 0.0318 |
| 0.0492 | 18.0 | 1836 | 0.0542 | 0.0248 | 0.0288 |
| 0.0486 | 19.0 | 1938 | 0.0631 | 0.0336 | 0.0369 |
| 0.047 | 20.0 | 2040 | 0.0482 | 0.0255 | 0.0290 |
| 0.0432 | 21.0 | 2142 | 0.0470 | 0.0262 | 0.0307 |
| 0.0433 | 22.0 | 2244 | 0.0460 | 0.0250 | 0.0290 |
| 0.0367 | 23.0 | 2346 | 0.0450 | 0.0253 | 0.0295 |
| 0.0343 | 24.0 | 2448 | 0.0444 | 0.0254 | 0.0283 |
| 0.0292 | 25.0 | 2550 | 0.0427 | 0.0248 | 0.0283 |
| 0.0261 | 26.0 | 2652 | 0.0409 | 0.0220 | 0.0250 |
| 0.025 | 27.0 | 2754 | 0.0360 | 0.0221 | 0.0251 |
| 0.0236 | 28.0 | 2856 | 0.0350 | 0.0208 | 0.0231 |
| 0.0222 | 29.0 | 2958 | 0.0338 | 0.0199 | 0.0222 |
| 0.0202 | 30.0 | 3060 | 0.0335 | 0.0199 | 0.0225 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
|