badrex
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xlsr-mk

@@ -1,199 +1,106 @@
 ---
-library_name: transformers
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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-mk
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_17_0
+      type: common_voice_17_0
+      config: mk
+      split: validation
+      args: mk
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.4437212531458821
 ---
+<!-- 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-hebrew/runs/dehxs1oz)
+# xlsr-mk
+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: 0.6273
+- Wer: 0.4437
+- Cer: 0.1074
+## 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    |
+|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
+| 3.541         | 1.8868  | 100  | 3.5532          | 1.0    | 1.0    |
+| 2.966         | 3.7736  | 200  | 2.9438          | 1.0    | 1.0    |
+| 2.298         | 5.6604  | 300  | 2.1673          | 1.0    | 0.7080 |
+| 0.5999        | 7.5472  | 400  | 0.7521          | 0.7476 | 0.2035 |
+| 0.3941        | 9.4340  | 500  | 0.7249          | 0.6911 | 0.1845 |
+| 0.2226        | 11.3208 | 600  | 0.6970          | 0.6602 | 0.1725 |
+| 0.3031        | 13.2075 | 700  | 0.7692          | 0.6506 | 0.1680 |
+| 0.1621        | 15.0943 | 800  | 0.7229          | 0.6232 | 0.1583 |
+| 0.2052        | 16.9811 | 900  | 0.6990          | 0.5722 | 0.1471 |
+| 0.1441        | 18.8679 | 1000 | 0.6829          | 0.5591 | 0.1400 |
+| 0.0548        | 20.7547 | 1100 | 0.6560          | 0.5309 | 0.1333 |
+| 0.1312        | 22.6415 | 1200 | 0.6590          | 0.5375 | 0.1332 |
+| 0.0582        | 24.5283 | 1300 | 0.7023          | 0.5268 | 0.1321 |
+| 0.1163        | 26.4151 | 1400 | 0.6900          | 0.5170 | 0.1293 |
+| 0.0491        | 28.3019 | 1500 | 0.6499          | 0.5089 | 0.1274 |
+| 0.063         | 30.1887 | 1600 | 0.6478          | 0.4869 | 0.1221 |
+| 0.0735        | 32.0755 | 1700 | 0.6678          | 0.4967 | 0.1256 |
+| 0.0437        | 33.9623 | 1800 | 0.6651          | 0.4803 | 0.1188 |
+| 0.0514        | 35.8491 | 1900 | 0.6741          | 0.4724 | 0.1168 |
+| 0.0306        | 37.7358 | 2000 | 0.6564          | 0.4717 | 0.1168 |
+| 0.0458        | 39.6226 | 2100 | 0.6428          | 0.4679 | 0.1140 |
+| 0.0398        | 41.5094 | 2200 | 0.6385          | 0.4531 | 0.1103 |
+| 0.0574        | 43.3962 | 2300 | 0.5991          | 0.4392 | 0.1063 |
+| 0.0481        | 45.2830 | 2400 | 0.6394          | 0.4468 | 0.1087 |
+| 0.0376        | 47.1698 | 2500 | 0.6184          | 0.4434 | 0.1072 |
+| 0.0275        | 49.0566 | 2600 | 0.6273          | 0.4437 | 0.1074 |
+### Framework versions
+- Transformers 4.42.0.dev0
+- Pytorch 2.3.1+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1