Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: facebook/w2v-bert-2.0
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: w2v-bert-2.0-igbo_naijavoices_100h
+  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-igbo_naijavoices_100h
+
+This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3933
+- Wer: 0.3094
+- Cer: 0.1373
+
+## 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: 3e-05
+- train_batch_size: 160
+- eval_batch_size: 160
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 2
+- total_train_batch_size: 320
+- total_eval_batch_size: 320
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 250.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Wer    | Cer    |
+|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
+| 0.638         | 3.4483  | 1000  | 0.6548          | 0.5546 | 0.2086 |
+| 0.4035        | 6.8966  | 2000  | 0.4278          | 0.3949 | 0.1574 |
+| 0.5526        | 10.3448 | 3000  | 0.3694          | 0.3530 | 0.1461 |
+| 0.305         | 13.7931 | 4000  | 0.3367          | 0.3357 | 0.1392 |
+| 0.2602        | 17.2414 | 5000  | 0.3230          | 0.3252 | 0.1366 |
+| 0.4161        | 20.6897 | 6000  | 0.3192          | 0.3226 | 0.1360 |
+| 0.2367        | 24.1379 | 7000  | 0.3196          | 0.3192 | 0.1345 |
+| 0.2463        | 27.5862 | 8000  | 0.3153          | 0.3089 | 0.1324 |
+| 0.1819        | 31.0345 | 9000  | 0.3187          | 0.3034 | 0.1334 |
+| 0.1852        | 34.4828 | 10000 | 0.3292          | 0.3067 | 0.1326 |
+| 0.1581        | 37.9310 | 11000 | 0.3510          | 0.2997 | 0.1310 |
+| 0.1455        | 41.3793 | 12000 | 0.3522          | 0.3080 | 0.1348 |
+| 0.0998        | 44.8276 | 13000 | 0.3933          | 0.3094 | 0.1373 |
+
+
+### Framework versions
+
+- Transformers 4.48.1
+- Pytorch 2.7.1+cu126
+- Datasets 4.0.0
+- Tokenizers 0.21.2

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