wav2vec2-large-mms-1b-barwar

README.md

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+---
+license: cc-by-nc-4.0
+base_model: facebook/mms-1b-all
+tags:
+- generated_from_trainer
+datasets:
+- nena_speech_1_0_test
+metrics:
+- wer
+model-index:
+- name: wav2vec2-large-mms-1b-barwar
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: nena_speech_1_0_test
+      type: nena_speech_1_0_test
+      config: barwar
+      split: test
+      args: barwar
+    metrics:
+    - name: Wer
+      type: wer
+      value: 1.0
+---
+
+<!-- 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-large-mms-1b-barwar
+
+This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the nena_speech_1_0_test dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.4355
+- Wer: 1.0
+- Cer: 0.3295
+
+## 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: 0.001
+- train_batch_size: 32
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
+| 16.2134       | 0.15  | 25   | 17.6705         | 1.0    | 1.1562 |
+| 6.1907        | 0.3   | 50   | 4.2262          | 0.9815 | 0.9986 |
+| 3.6438        | 0.45  | 75   | 4.1625          | 1.0    | 0.7804 |
+| 3.1627        | 0.6   | 100  | 4.1537          | 1.0    | 0.4727 |
+| 2.2322        | 0.75  | 125  | 3.8028          | 1.0    | 0.4554 |
+| 3.0705        | 0.9   | 150  | 3.3680          | 1.0    | 0.4352 |
+| 2.9176        | 1.05  | 175  | 3.2934          | 1.0    | 0.4279 |
+| 2.2255        | 1.2   | 200  | 3.6359          | 1.0    | 0.3926 |
+| 2.4518        | 1.35  | 225  | 3.2249          | 1.0    | 0.3863 |
+| 1.9254        | 1.5   | 250  | 3.7029          | 1.0    | 0.3875 |
+| 2.7212        | 1.65  | 275  | 3.5201          | 1.0    | 0.3673 |
+| 2.7976        | 1.8   | 300  | 3.3253          | 1.0    | 0.3986 |
+| 2.0545        | 1.95  | 325  | 3.6138          | 1.0    | 0.3554 |
+| 2.3335        | 2.1   | 350  | 3.5161          | 1.0    | 0.3554 |
+| 2.0049        | 2.25  | 375  | 3.4727          | 1.0    | 0.3543 |
+| 2.8896        | 2.4   | 400  | 3.2484          | 1.0    | 0.3535 |
+| 1.9641        | 2.54  | 425  | 3.4330          | 1.0    | 0.3485 |
+| 1.9649        | 2.69  | 450  | 3.8596          | 1.0    | 0.3444 |
+| 2.0422        | 2.84  | 475  | 3.4291          | 1.0    | 0.3506 |
+| 2.4093        | 2.99  | 500  | 3.3137          | 1.0    | 0.3434 |
+| 1.8187        | 3.14  | 525  | 3.4423          | 1.0    | 0.3415 |
+| 1.7495        | 3.29  | 550  | 3.5614          | 1.0    | 0.3431 |
+| 2.0658        | 3.44  | 575  | 3.0324          | 1.0    | 0.3543 |
+| 1.5128        | 3.59  | 600  | 3.6654          | 1.0    | 0.3452 |
+| 1.7876        | 3.74  | 625  | 3.8747          | 1.0    | 0.3388 |
+| 3.8652        | 3.89  | 650  | 2.9874          | 1.0    | 0.3387 |
+| 2.8945        | 4.04  | 675  | 3.3015          | 1.0    | 0.3344 |
+| 1.9763        | 4.19  | 700  | 3.1970          | 1.0    | 0.3389 |
+| 2.0538        | 4.34  | 725  | 3.4811          | 1.0    | 0.3316 |
+| 1.7723        | 4.49  | 750  | 3.6706          | 1.0    | 0.3305 |
+| 2.0489        | 4.64  | 775  | 3.4281          | 1.0    | 0.3312 |
+| 2.555         | 4.79  | 800  | 3.2610          | 1.0    | 0.3341 |
+| 1.6591        | 4.94  | 825  | 3.4355          | 1.0    | 0.3295 |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.6
+- Tokenizers 0.14.1

adapter.aii.safetensors

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preprocessor_config.json

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+{
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": true,
+  "sampling_rate": 16000
+}

training_args.bin

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