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mHuBERT-147upper-sorbian

@@ -1,199 +1,105 @@
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-library_name: transformers
-tags: []
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-# Model Card for Model ID
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 ---
+license: cc-by-nc-4.0
+base_model: utter-project/mHuBERT-147
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: mHuBERT-147upper-sorbian
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: common_voice_17_0
+      config: hsb
+      split: validation
+      args: hsb
+    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. -->
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning-new/runs/nkb11lep)
+# mHuBERT-147upper-sorbian
+This model is a fine-tuned version of [utter-project/mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147) on the common_voice_17_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 3.2170
+- Wer: 1.0
+- Cer: 1.0
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 100
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch   | Step | Validation Loss | Wer | Cer |
+|:-------------:|:-------:|:----:|:---------------:|:---:|:---:|
+| 7.2839        | 3.9216  | 100  | 7.4925          | 1.0 | 1.0 |
+| 3.4632        | 7.8431  | 200  | 3.4671          | 1.0 | 1.0 |
+| 3.181         | 11.7647 | 300  | 3.2306          | 1.0 | 1.0 |
+| 3.2284        | 15.6863 | 400  | 3.2231          | 1.0 | 1.0 |
+| 3.2113        | 19.6078 | 500  | 3.2243          | 1.0 | 1.0 |
+| 3.1844        | 23.5294 | 600  | 3.2183          | 1.0 | 1.0 |
+| 3.2644        | 27.4510 | 700  | 3.2180          | 1.0 | 1.0 |
+| 3.2111        | 31.3725 | 800  | 3.2191          | 1.0 | 1.0 |
+| 3.187         | 35.2941 | 900  | 3.2189          | 1.0 | 1.0 |
+| 3.2133        | 39.2157 | 1000 | 3.2203          | 1.0 | 1.0 |
+| 3.2406        | 43.1373 | 1100 | 3.2181          | 1.0 | 1.0 |
+| 3.1993        | 47.0588 | 1200 | 3.2178          | 1.0 | 1.0 |
+| 3.2036        | 50.9804 | 1300 | 3.2169          | 1.0 | 1.0 |
+| 3.2283        | 54.9020 | 1400 | 3.2171          | 1.0 | 1.0 |
+| 3.1854        | 58.8235 | 1500 | 3.2198          | 1.0 | 1.0 |
+| 3.184         | 62.7451 | 1600 | 3.2182          | 1.0 | 1.0 |
+| 3.2253        | 66.6667 | 1700 | 3.2194          | 1.0 | 1.0 |
+| 3.1943        | 70.5882 | 1800 | 3.2194          | 1.0 | 1.0 |
+| 3.201         | 74.5098 | 1900 | 3.2167          | 1.0 | 1.0 |
+| 3.2178        | 78.4314 | 2000 | 3.2180          | 1.0 | 1.0 |
+| 3.2252        | 82.3529 | 2100 | 3.2172          | 1.0 | 1.0 |
+| 3.2081        | 86.2745 | 2200 | 3.2170          | 1.0 | 1.0 |
+| 3.2125        | 90.1961 | 2300 | 3.2170          | 1.0 | 1.0 |
+| 3.23          | 94.1176 | 2400 | 3.2170          | 1.0 | 1.0 |
+| 3.1851        | 98.0392 | 2500 | 3.2170          | 1.0 | 1.0 |
+### Framework versions
+- Transformers 4.42.0.dev0
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1