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mHuBERT-147-upper-sorbian

@@ -1,199 +1,105 @@
 ---
-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-147-upper-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/41am9hha)
+# mHuBERT-147-upper-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: 3.3582
+- 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: 1e-05
+- 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    |
+|:-------------:|:-------:|:----:|:---------------:|:---:|:------:|
+| 15.5448       | 3.9216  | 100  | 16.7511         | 1.0 | 2.0768 |
+| 10.1433       | 7.8431  | 200  | 10.5841         | 1.0 | 1.0    |
+| 8.264         | 11.7647 | 300  | 8.8218          | 1.0 | 1.0    |
+| 7.9924        | 15.6863 | 400  | 8.2091          | 1.0 | 1.0    |
+| 7.1304        | 19.6078 | 500  | 7.5249          | 1.0 | 1.0    |
+| 6.2453        | 23.5294 | 600  | 6.8211          | 1.0 | 1.0    |
+| 6.2833        | 27.4510 | 700  | 6.1921          | 1.0 | 1.0    |
+| 5.3658        | 31.3725 | 800  | 5.6396          | 1.0 | 1.0    |
+| 4.8314        | 35.2941 | 900  | 5.1645          | 1.0 | 1.0    |
+| 4.8285        | 39.2157 | 1000 | 4.7647          | 1.0 | 1.0    |
+| 4.2474        | 43.1373 | 1100 | 4.4360          | 1.0 | 1.0    |
+| 3.9898        | 47.0588 | 1200 | 4.1735          | 1.0 | 1.0    |
+| 3.8997        | 50.9804 | 1300 | 3.9678          | 1.0 | 1.0    |
+| 3.7723        | 54.9020 | 1400 | 3.8085          | 1.0 | 1.0    |
+| 3.6148        | 58.8235 | 1500 | 3.6879          | 1.0 | 1.0    |
+| 3.4969        | 62.7451 | 1600 | 3.5966          | 1.0 | 1.0    |
+| 3.5233        | 66.6667 | 1700 | 3.5286          | 1.0 | 1.0    |
+| 3.4324        | 70.5882 | 1800 | 3.4771          | 1.0 | 1.0    |
+| 3.393         | 74.5098 | 1900 | 3.4387          | 1.0 | 1.0    |
+| 3.3967        | 78.4314 | 2000 | 3.4102          | 1.0 | 1.0    |
+| 3.3846        | 82.3529 | 2100 | 3.3891          | 1.0 | 1.0    |
+| 3.3431        | 86.2745 | 2200 | 3.3746          | 1.0 | 1.0    |
+| 3.3601        | 90.1961 | 2300 | 3.3653          | 1.0 | 1.0    |
+| 3.3545        | 94.1176 | 2400 | 3.3599          | 1.0 | 1.0    |
+| 3.3114        | 98.0392 | 2500 | 3.3582          | 1.0 | 1.0    |
+### Framework versions
+- Transformers 4.42.0.dev0
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1