Model save

README.md

@@ -8,60 +8,65 @@ model-index:
 - name: whisper-large-v3-mn-ft
   results: []
 ---
-
-<!-- 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. -->
-
-# whisper-large-v3-mn-ft
-
-This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5429
-
-## 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: 0.0001
-- train_batch_size: 4
-- eval_batch_size: 4
-- seed: 42
-- gradient_accumulation_steps: 4
-- total_train_batch_size: 16
-- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 500
-- num_epochs: 3.0
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss |
-|:-------------:|:------:|:----:|:---------------:|
-| 2.4317        | 0.5903 | 500  | 0.7475          |
-| 1.1836        | 1.1806 | 1000 | 0.5816          |
-| 0.8169        | 1.7710 | 1500 | 0.5508          |
-| 0.5782        | 2.3613 | 2000 | 0.5468          |
-| 0.4928        | 2.9516 | 2500 | 0.5429          |
-
-
-### Framework versions
-
-- PEFT 0.5.0
-- Transformers 4.51.3
-- Pytorch 2.7.0+cu118
-- Datasets 3.5.0
-- Tokenizers 0.21.1
+
+<!-- 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. -->
+
+# whisper-large-v3-mn-ft
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5834
+
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 6.0
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.4317        | 0.5903 | 500  | 0.7475          |
+| 1.1836        | 1.1806 | 1000 | 0.5816          |
+| 0.8169        | 1.7710 | 1500 | 0.5508          |
+| 0.5782        | 2.3613 | 2000 | 0.5468          |
+| 0.4928        | 2.9516 | 2500 | 0.5429          |
+| 0.444         | 3.5419 | 3000 | 0.5626          |
+| 0.2888        | 4.1322 | 3500 | 0.5678          |
+| 0.283         | 4.7226 | 4000 | 0.5710          |
+| 0.1823        | 5.3129 | 4500 | 0.5852          |
+| 0.1725        | 5.9032 | 5000 | 0.5834          |
+
+
+### Framework versions
+
+- PEFT 0.15.2
+- Transformers 4.51.3
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.5
+- Tokenizers 0.21.1