Model save

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: asr-africa/wav2vec2-xls-r-ewe-100-hours
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: Wav2vec2-afr
+  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-afr
+
+This model is a fine-tuned version of [asr-africa/wav2vec2-xls-r-ewe-100-hours](https://huggingface.co/asr-africa/wav2vec2-xls-r-ewe-100-hours) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1908
+- Wer: 0.2050
+
+## 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: 2
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 16
+- 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_steps: 500
+- num_epochs: 60.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
+|:-------------:|:------:|:-----:|:---------------:|:------:|
+| 0.2638        | 0.3017 | 500   | 0.3208          | 0.3275 |
+| 0.1603        | 0.6034 | 1000  | 0.2497          | 0.2649 |
+| 0.142         | 0.9050 | 1500  | 0.2145          | 0.2488 |
+| 0.1645        | 1.2064 | 2000  | 0.2023          | 0.2252 |
+| 0.1818        | 1.5080 | 2500  | 0.1984          | 0.2177 |
+| 0.1827        | 1.8097 | 3000  | 0.1995          | 0.2204 |
+| 0.1859        | 2.1110 | 3500  | 0.1994          | 0.2240 |
+| 0.2488        | 2.4127 | 4000  | 0.2040          | 0.2250 |
+| 0.2292        | 2.7144 | 4500  | 0.1991          | 0.2260 |
+| 0.2489        | 3.0157 | 5000  | 0.1845          | 0.2137 |
+| 0.4731        | 3.3174 | 5500  | 0.1854          | 0.2121 |
+| 0.2497        | 3.6191 | 6000  | 0.1888          | 0.2102 |
+| 0.2872        | 3.9207 | 6500  | 0.1915          | 0.2197 |
+| 0.248         | 4.2220 | 7000  | 0.1920          | 0.2199 |
+| 0.2048        | 4.5237 | 7500  | 0.1822          | 0.2055 |
+| 0.1977        | 4.8254 | 8000  | 0.1850          | 0.2094 |
+| 0.1459        | 5.1267 | 8500  | 0.1905          | 0.2153 |
+| 0.1471        | 5.4284 | 9000  | 0.1864          | 0.2023 |
+| 0.1528        | 5.7301 | 9500  | 0.1829          | 0.2089 |
+| 0.0668        | 6.0314 | 10000 | 0.1908          | 0.2050 |
+
+
+### Framework versions
+
+- Transformers 4.50.3
+- Pytorch 2.7.0+cu126
+- Datasets 3.5.0
+- Tokenizers 0.21.1

model.safetensors

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