badrex
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xlsr-128upper-sorbian

@@ -1,199 +1,92 @@
 ---
-library_name: transformers
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 ---
-# Model Card for Model ID
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 ---
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_17_0
+metrics:
+- wer
+model-index:
+- name: xlsr-128upper-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: 0.549367088607595
 ---
+<!-- 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/xhato0mz)
+# xlsr-128upper-sorbian
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7110
+- Wer: 0.5494
+- Cer: 0.1188
+## 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: 50
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
+| 3.8492        | 3.9216  | 100  | 3.9919          | 1.0    | 1.0    |
+| 3.1983        | 7.8431  | 200  | 3.2332          | 1.0    | 1.0    |
+| 2.9601        | 11.7647 | 300  | 3.0166          | 0.9873 | 0.9798 |
+| 0.4618        | 15.6863 | 400  | 0.7749          | 0.7557 | 0.1917 |
+| 0.2411        | 19.6078 | 500  | 0.7812          | 0.7013 | 0.1702 |
+| 0.1112        | 23.5294 | 600  | 0.7275          | 0.6405 | 0.1508 |
+| 0.1108        | 27.4510 | 700  | 0.7995          | 0.6247 | 0.1440 |
+| 0.0432        | 31.3725 | 800  | 0.7902          | 0.6139 | 0.1432 |
+| 0.0431        | 35.2941 | 900  | 0.7615          | 0.5797 | 0.1372 |
+| 0.0515        | 39.2157 | 1000 | 0.7029          | 0.5456 | 0.1234 |
+| 0.0241        | 43.1373 | 1100 | 0.7296          | 0.5285 | 0.1188 |
+| 0.0342        | 47.0588 | 1200 | 0.7110          | 0.5494 | 0.1188 |
+### Framework versions
+- Transformers 4.42.0.dev0
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1