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wav2vec2-xlsr-ln-50hr-v1

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 ---
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: wav2vec2-xlsr-ln-50hr-v1
+  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-xlsr-ln-50hr-v1
+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: 0.5500
+- Model Preparation Time: 0.0092
+- Wer: 0.2237
+- Cer: 0.0739
+## 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: 0.0003
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 120
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch   | Step  | Validation Loss | Model Preparation Time | Wer    | Cer    |
+|:-------------:|:-------:|:-----:|:---------------:|:----------------------:|:------:|:------:|
+| 4.1139        | 0.9986  | 362   | 0.5868          | 0.0092                 | 0.4335 | 0.1216 |
+| 0.3001        | 2.0     | 725   | 0.3474          | 0.0092                 | 0.2614 | 0.0792 |
+| 0.2033        | 2.9986  | 1087  | 0.3256          | 0.0092                 | 0.2023 | 0.0670 |
+| 0.1629        | 4.0     | 1450  | 0.3155          | 0.0092                 | 0.2089 | 0.0641 |
+| 0.1366        | 4.9986  | 1812  | 0.2904          | 0.0092                 | 0.1899 | 0.0577 |
+| 0.1182        | 6.0     | 2175  | 0.2895          | 0.0092                 | 0.1864 | 0.0572 |
+| 0.1064        | 6.9986  | 2537  | 0.2815          | 0.0092                 | 0.1671 | 0.0535 |
+| 0.0945        | 8.0     | 2900  | 0.3037          | 0.0092                 | 0.1706 | 0.0559 |
+| 0.0845        | 8.9986  | 3262  | 0.3142          | 0.0092                 | 0.1743 | 0.0581 |
+| 0.0779        | 10.0    | 3625  | 0.3031          | 0.0092                 | 0.1758 | 0.0572 |
+| 0.0754        | 10.9986 | 3987  | 0.3111          | 0.0092                 | 0.1704 | 0.0568 |
+| 0.0687        | 12.0    | 4350  | 0.3130          | 0.0092                 | 0.1664 | 0.0539 |
+| 0.0582        | 12.9986 | 4712  | 0.3364          | 0.0092                 | 0.1619 | 0.0526 |
+| 0.0552        | 14.0    | 5075  | 0.3039          | 0.0092                 | 0.1568 | 0.0527 |
+| 0.054         | 14.9986 | 5437  | 0.3176          | 0.0092                 | 0.1561 | 0.0507 |
+| 0.0453        | 16.0    | 5800  | 0.3283          | 0.0092                 | 0.1550 | 0.0519 |
+| 0.046         | 16.9986 | 6162  | 0.3320          | 0.0092                 | 0.1556 | 0.0504 |
+| 0.0443        | 18.0    | 6525  | 0.3443          | 0.0092                 | 0.1560 | 0.0510 |
+| 0.0441        | 18.9986 | 6887  | 0.3392          | 0.0092                 | 0.1549 | 0.0518 |
+| 0.0375        | 20.0    | 7250  | 0.3526          | 0.0092                 | 0.1565 | 0.0529 |
+| 0.0371        | 20.9986 | 7612  | 0.3552          | 0.0092                 | 0.1574 | 0.0541 |
+| 0.0412        | 22.0    | 7975  | 0.3313          | 0.0092                 | 0.1762 | 0.0565 |
+| 0.041         | 22.9986 | 8337  | 0.3649          | 0.0092                 | 0.1695 | 0.0572 |
+| 0.0377        | 24.0    | 8700  | 0.3603          | 0.0092                 | 0.1578 | 0.0532 |
+| 0.0332        | 24.9986 | 9062  | 0.3496          | 0.0092                 | 0.1513 | 0.0509 |
+| 0.032         | 26.0    | 9425  | 0.3436          | 0.0092                 | 0.1504 | 0.0517 |
+| 0.0314        | 26.9986 | 9787  | 0.3573          | 0.0092                 | 0.1545 | 0.0523 |
+| 0.0281        | 28.0    | 10150 | 0.3644          | 0.0092                 | 0.1504 | 0.0504 |
+| 0.0268        | 28.9986 | 10512 | 0.3628          | 0.0092                 | 0.1521 | 0.0506 |
+| 0.0304        | 30.0    | 10875 | 0.3692          | 0.0092                 | 0.1512 | 0.0510 |
+| 0.0296        | 30.9986 | 11237 | 0.3573          | 0.0092                 | 0.1493 | 0.0505 |
+| 0.023         | 32.0    | 11600 | 0.3767          | 0.0092                 | 0.1562 | 0.0516 |
+| 0.0292        | 32.9986 | 11962 | 0.3462          | 0.0092                 | 0.1496 | 0.0492 |
+| 0.0261        | 34.0    | 12325 | 0.3927          | 0.0092                 | 0.1500 | 0.0490 |
+| 0.0248        | 34.9986 | 12687 | 0.3771          | 0.0092                 | 0.1438 | 0.0492 |
+| 0.0238        | 36.0    | 13050 | 0.3763          | 0.0092                 | 0.1457 | 0.0474 |
+| 0.0223        | 36.9986 | 13412 | 0.3627          | 0.0092                 | 0.1523 | 0.0510 |
+| 0.0225        | 38.0    | 13775 | 0.3825          | 0.0092                 | 0.1468 | 0.0494 |
+| 0.022         | 38.9986 | 14137 | 0.3830          | 0.0092                 | 0.1614 | 0.0547 |
+| 0.0226        | 40.0    | 14500 | 0.3851          | 0.0092                 | 0.1488 | 0.0509 |
+| 0.0225        | 40.9986 | 14862 | 0.4072          | 0.0092                 | 0.1592 | 0.0530 |
+| 0.0197        | 42.0    | 15225 | 0.4024          | 0.0092                 | 0.1460 | 0.0502 |
+| 0.0205        | 42.9986 | 15587 | 0.4099          | 0.0092                 | 0.1491 | 0.0510 |
+| 0.0195        | 44.0    | 15950 | 0.3746          | 0.0092                 | 0.1449 | 0.0501 |
+| 0.0187        | 44.9986 | 16312 | 0.3902          | 0.0092                 | 0.1417 | 0.0487 |
+| 0.0196        | 46.0    | 16675 | 0.3923          | 0.0092                 | 0.1453 | 0.0497 |
+| 0.0177        | 46.9986 | 17037 | 0.4107          | 0.0092                 | 0.1458 | 0.0490 |
+| 0.0175        | 48.0    | 17400 | 0.4043          | 0.0092                 | 0.1478 | 0.0503 |
+| 0.0178        | 48.9986 | 17762 | 0.4009          | 0.0092                 | 0.1450 | 0.0514 |
+| 0.0161        | 50.0    | 18125 | 0.4172          | 0.0092                 | 0.1374 | 0.0472 |
+| 0.015         | 50.9986 | 18487 | 0.4006          | 0.0092                 | 0.1342 | 0.0463 |
+| 0.015         | 52.0    | 18850 | 0.3975          | 0.0092                 | 0.1399 | 0.0492 |
+| 0.0173        | 52.9986 | 19212 | 0.3690          | 0.0092                 | 0.1399 | 0.0493 |
+| 0.0156        | 54.0    | 19575 | 0.4321          | 0.0092                 | 0.1439 | 0.0504 |
+| 0.0151        | 54.9986 | 19937 | 0.4353          | 0.0092                 | 0.1443 | 0.0508 |
+| 0.0151        | 56.0    | 20300 | 0.3784          | 0.0092                 | 0.1394 | 0.0488 |
+| 0.015         | 56.9986 | 20662 | 0.4225          | 0.0092                 | 0.1415 | 0.0499 |
+| 0.0128        | 58.0    | 21025 | 0.4172          | 0.0092                 | 0.1421 | 0.0486 |
+| 0.0124        | 58.9986 | 21387 | 0.3899          | 0.0092                 | 0.1400 | 0.0479 |
+| 0.0109        | 60.0    | 21750 | 0.4265          | 0.0092                 | 0.1364 | 0.0468 |
+| 0.0109        | 60.9986 | 22112 | 0.4143          | 0.0092                 | 0.1400 | 0.0486 |
+| 0.0118        | 62.0    | 22475 | 0.4204          | 0.0092                 | 0.1446 | 0.0495 |
+| 0.0125        | 62.9986 | 22837 | 0.4020          | 0.0092                 | 0.1367 | 0.0472 |
+### Framework versions
+- Transformers 4.43.3
+- Pytorch 2.1.0+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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