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xls-r-300-cv17-upper-sorbian-adap-pl

@@ -1,199 +1,105 @@
 ---
-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: xls-r-300-cv17-upper-sorbian-adap-pl
+  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: 0.5708860759493671
 ---
+<!-- 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-polish/runs/3sjnh0u1)
+# xls-r-300-cv17-upper-sorbian-adap-pl
+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: 0.8568
+- Wer: 0.5709
+- Cer: 0.1289
+## 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    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
+| 3.3238        | 3.9216  | 100  | 3.2936          | 1.0    | 1.0    |
+| 1.9138        | 7.8431  | 200  | 2.0272          | 1.0    | 0.5746 |
+| 0.3833        | 11.7647 | 300  | 0.8755          | 0.8329 | 0.2162 |
+| 0.2008        | 15.6863 | 400  | 0.9388          | 0.8171 | 0.2115 |
+| 0.2055        | 19.6078 | 500  | 0.9805          | 0.7905 | 0.2056 |
+| 0.1012        | 23.5294 | 600  | 1.0175          | 0.7867 | 0.2035 |
+| 0.1244        | 27.4510 | 700  | 0.9544          | 0.7241 | 0.1756 |
+| 0.0778        | 31.3725 | 800  | 1.0507          | 0.7576 | 0.1885 |
+| 0.0531        | 35.2941 | 900  | 0.9845          | 0.7177 | 0.1727 |
+| 0.0725        | 39.2157 | 1000 | 0.9131          | 0.7044 | 0.1681 |
+| 0.0363        | 43.1373 | 1100 | 0.8816          | 0.6487 | 0.1543 |
+| 0.0429        | 47.0588 | 1200 | 0.8909          | 0.6304 | 0.1498 |
+| 0.0409        | 50.9804 | 1300 | 0.9260          | 0.6538 | 0.1581 |
+| 0.0288        | 54.9020 | 1400 | 0.8264          | 0.6006 | 0.1373 |
+| 0.04          | 58.8235 | 1500 | 0.8709          | 0.6234 | 0.1446 |
+| 0.0251        | 62.7451 | 1600 | 0.8296          | 0.5905 | 0.1359 |
+| 0.0294        | 66.6667 | 1700 | 0.8679          | 0.6044 | 0.1398 |
+| 0.0247        | 70.5882 | 1800 | 0.8638          | 0.5994 | 0.1353 |
+| 0.0135        | 74.5098 | 1900 | 0.8419          | 0.5861 | 0.1338 |
+| 0.0423        | 78.4314 | 2000 | 0.8880          | 0.5987 | 0.1382 |
+| 0.0216        | 82.3529 | 2100 | 0.8557          | 0.5728 | 0.1312 |
+| 0.0126        | 86.2745 | 2200 | 0.8650          | 0.5703 | 0.1303 |
+| 0.0113        | 90.1961 | 2300 | 0.8498          | 0.5816 | 0.1314 |
+| 0.0191        | 94.1176 | 2400 | 0.8653          | 0.5816 | 0.1316 |
+| 0.0195        | 98.0392 | 2500 | 0.8568          | 0.5709 | 0.1289 |
+### Framework versions
+- Transformers 4.42.0.dev0
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1