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w2v-bert-2.0-ln-afrivoice-10hr-v3

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wav2vec2-bert

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KasuleTrevor commited on Aug 21, 2024

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 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-ln-afrivoice-10hr-v3
+  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. -->
+# w2v-bert-2.0-ln-afrivoice-10hr-v3
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5394
+- Model Preparation Time: 0.0157
+- Wer: 0.2805
+- Cer: 0.0704
+## 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: 5e-05
+- 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_ratio: 0.033
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch   | Step | Validation Loss | Model Preparation Time | Wer    | Cer    |
+|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:------:|:------:|
+| 4.8449        | 0.9919  | 61   | 2.7369          | 0.0157                 | 0.9995 | 0.9870 |
+| 1.9412        | 2.0     | 123  | 0.9095          | 0.0157                 | 0.4841 | 0.1700 |
+| 0.7831        | 2.9919  | 184  | 0.8914          | 0.0157                 | 0.4018 | 0.1424 |
+| 0.67          | 4.0     | 246  | 0.7633          | 0.0157                 | 0.3919 | 0.1391 |
+| 0.5982        | 4.9919  | 307  | 0.8712          | 0.0157                 | 0.3514 | 0.1349 |
+| 0.5577        | 6.0     | 369  | 0.6596          | 0.0157                 | 0.4425 | 0.1566 |
+| 0.4945        | 6.9919  | 430  | 0.7157          | 0.0157                 | 0.3838 | 0.1419 |
+| 0.4363        | 8.0     | 492  | 0.7981          | 0.0157                 | 0.3582 | 0.1324 |
+| 0.395         | 8.9919  | 553  | 0.7956          | 0.0157                 | 0.3483 | 0.1310 |
+| 0.3416        | 10.0    | 615  | 0.7110          | 0.0157                 | 0.4082 | 0.1571 |
+| 0.3181        | 10.9919 | 676  | 0.8728          | 0.0157                 | 0.3680 | 0.1334 |
+| 0.2837        | 12.0    | 738  | 0.8389          | 0.0157                 | 0.3656 | 0.1361 |
+| 0.2482        | 12.9919 | 799  | 0.9984          | 0.0157                 | 0.3582 | 0.1296 |
+| 0.224         | 14.0    | 861  | 0.8696          | 0.0157                 | 0.3971 | 0.1515 |
+| 0.204         | 14.9919 | 922  | 1.0671          | 0.0157                 | 0.3563 | 0.1312 |
+| 0.1665        | 16.0    | 984  | 1.0956          | 0.0157                 | 0.3622 | 0.1329 |
+| 0.1507        | 16.9919 | 1045 | 1.4699          | 0.0157                 | 0.3481 | 0.1297 |
+| 0.1144        | 18.0    | 1107 | 1.4821          | 0.0157                 | 0.3566 | 0.1299 |
+| 0.1327        | 18.9919 | 1168 | 1.2253          | 0.0157                 | 0.3699 | 0.1352 |
+| 0.1085        | 20.0    | 1230 | 1.2042          | 0.0157                 | 0.3929 | 0.1452 |
+| 0.0694        | 20.9919 | 1291 | 1.4515          | 0.0157                 | 0.3681 | 0.1317 |
+| 0.0476        | 22.0    | 1353 | 1.5795          | 0.0157                 | 0.3551 | 0.1301 |
+| 0.0357        | 22.9919 | 1414 | 1.5949          | 0.0157                 | 0.3527 | 0.1300 |
+| 0.0241        | 24.0    | 1476 | 1.7094          | 0.0157                 | 0.3555 | 0.1304 |
+| 0.017         | 24.9919 | 1537 | 1.7941          | 0.0157                 | 0.3577 | 0.1311 |
+| 0.0128        | 26.0    | 1599 | 1.8157          | 0.0157                 | 0.3555 | 0.1300 |
+| 0.0132        | 26.9919 | 1660 | 1.8541          | 0.0157                 | 0.3621 | 0.1324 |
+### Framework versions
+- Transformers 4.44.0
+- Pytorch 2.1.0+cu118
+- Datasets 2.20.0
+- Tokenizers 0.19.1

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