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-hausa_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-hausa_naijavoices_100h
+
+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: 0.3840
+- Wer: 0.3541
+- Cer: 0.1939
+
+## 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 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    |
+|:-------------:|:-------:|:-----:|:---------------:|:------:|:------:|
+| 0.346         | 2.7933  | 1000  | 0.4367          | 0.4197 | 0.2131 |
+| 0.2972        | 5.5866  | 2000  | 0.3150          | 0.3691 | 0.1998 |
+| 0.2638        | 8.3799  | 3000  | 0.2892          | 0.3556 | 0.1959 |
+| 0.2308        | 11.1732 | 4000  | 0.2728          | 0.3471 | 0.1938 |
+| 0.2338        | 13.9665 | 5000  | 0.2707          | 0.3430 | 0.1929 |
+| 0.2105        | 16.7598 | 6000  | 0.2687          | 0.3389 | 0.1917 |
+| 0.1732        | 19.5531 | 7000  | 0.2710          | 0.3437 | 0.1935 |
+| 0.1638        | 22.3464 | 8000  | 0.2657          | 0.3426 | 0.1927 |
+| 0.1933        | 25.1397 | 9000  | 0.2787          | 0.3413 | 0.1918 |
+| 0.144         | 27.9330 | 10000 | 0.2651          | 0.3397 | 0.1916 |
+| 0.1493        | 30.7263 | 11000 | 0.2757          | 0.3415 | 0.1923 |
+| 0.1267        | 33.5196 | 12000 | 0.2826          | 0.3482 | 0.1924 |
+| 0.1045        | 36.3128 | 13000 | 0.3057          | 0.3480 | 0.1930 |
+| 0.066         | 39.1061 | 14000 | 0.3314          | 0.3526 | 0.1942 |
+| 0.0564        | 41.8994 | 15000 | 0.3840          | 0.3541 | 0.1939 |
+
+
+### Framework versions
+
+- Transformers 4.48.1
+- Pytorch 2.6.0+cu124
+- Datasets 3.5.0
+- Tokenizers 0.21.1

model.safetensors

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