End of training

README.md

@@ -1,3 +1,83 @@
 ---
-license: apache-2.0
+base_model: ylacombe/w2v-bert-2.0-600m-turkish-colab
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_16_0
+metrics:
+- wer
+model-index:
+- name: mactest2
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_16_0
+      type: common_voice_16_0
+      config: tr
+      split: test
+      args: tr
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.3088954056695992
 ---
+
+<!-- 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. -->
+
+# mactest2
+
+This model is a fine-tuned version of [ylacombe/w2v-bert-2.0-600m-turkish-colab](https://huggingface.co/ylacombe/w2v-bert-2.0-600m-turkish-colab) on the common_voice_16_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5663
+- Wer: 0.3089
+
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 150
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.305         | 1.6   | 100  | 0.4562          | 0.2952 |
+| 0.0505        | 3.2   | 200  | 0.4923          | 0.3284 |
+| 0.0298        | 4.8   | 300  | 0.4925          | 0.3157 |
+| 0.0156        | 6.4   | 400  | 0.5194          | 0.3069 |
+| 0.0058        | 8.0   | 500  | 0.5420          | 0.3050 |
+| 0.004         | 9.6   | 600  | 0.5663          | 0.3089 |
+
+
+### Framework versions
+
+- Transformers 4.37.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

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