Model save

README.md

@@ -0,0 +1,86 @@
+---
+license: cc-by-nc-4.0
+base_model: facebook/mms-1b-all
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_16_0
+metrics:
+- wer
+model-index:
+- name: breeze-listen-w2v2-ml
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_16_0
+      type: common_voice_16_0
+      config: ml
+      split: test
+      args: ml
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.5345542501727713
+---
+
+<!-- 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. -->
+
+# breeze-listen-w2v2-ml
+
+This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2698
+- Wer: 0.5346
+
+## 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: 4
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 4.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| No log        | 0.41  | 200  | 5.4728          | 1.0757 |
+| No log        | 0.81  | 400  | 5.1274          | 1.0038 |
+| 6.5037        | 1.22  | 600  | 0.6167          | 0.8131 |
+| 6.5037        | 1.63  | 800  | 0.3284          | 0.5829 |
+| 1.0482        | 2.03  | 1000 | 0.3169          | 0.5667 |
+| 1.0482        | 2.44  | 1200 | 0.2876          | 0.5425 |
+| 1.0482        | 2.85  | 1400 | 0.2847          | 0.5522 |
+| 0.4314        | 3.25  | 1600 | 0.2746          | 0.5394 |
+| 0.4314        | 3.66  | 1800 | 0.2698          | 0.5346 |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.1

breeze-listen-w2v2-ml.log

@@ -130,3 +130,5 @@ weight_decay=0.0,
 {'eval_loss': 0.2846720516681671, 'eval_wer': 0.5521769177608846, 'eval_runtime': 161.8788, 'eval_samples_per_second': 4.096, 'eval_steps_per_second': 0.513, 'epoch': 2.85}
 {'loss': 0.4314, 'learning_rate': 0.00025374732334047106, 'epoch': 3.05}
 {'eval_loss': 0.27460750937461853, 'eval_wer': 0.5393918451969593, 'eval_runtime': 160.7333, 'eval_samples_per_second': 4.125, 'eval_steps_per_second': 0.516, 'epoch': 3.25}
+{'eval_loss': 0.26981213688850403, 'eval_wer': 0.5345542501727713, 'eval_runtime': 160.1257, 'eval_samples_per_second': 4.14, 'eval_steps_per_second': 0.518, 'epoch': 3.66}
+{'train_runtime': 5112.0325, 'train_samples_per_second': 1.54, 'train_steps_per_second': 0.385, 'train_loss': 2.1205503649827913, 'epoch': 4.0}

model.safetensors

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