End of training

README.md

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+---
+language:
+- el
+license: apache-2.0
+base_model: openai/whisper-base
+tags:
+- generated_from_trainer
+datasets:
+- AMoustakis/test-dataset
+metrics:
+- wer
+model-index:
+- name: Whisper Base Greek
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Test Dataset for greek language
+      type: AMoustakis/test-dataset
+      args: 'split: train'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 61.77777777777778
+---
+
+<!-- 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 Base Greek
+
+This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Test Dataset for greek language dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2675
+- Wer: 61.7778
+
+## 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: 0.001
+- train_batch_size: 3
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.9014        | 1.0   | 4    | 0.5733          | 74.5185 |
+| 0.4829        | 2.0   | 8    | 0.4158          | 64.4444 |
+| 0.5963        | 3.0   | 12   | 0.3257          | 65.0370 |
+| 0.3399        | 4.0   | 16   | 0.2857          | 61.7778 |
+| 0.4436        | 5.0   | 20   | 0.2675          | 61.7778 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

preprocessor_config.json

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+{
+  "chunk_length": 30,
+  "feature_extractor_type": "WhisperFeatureExtractor",
+  "feature_size": 80,
+  "hop_length": 160,
+  "n_fft": 400,
+  "n_samples": 480000,
+  "nb_max_frames": 3000,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "processor_class": "WhisperProcessor",
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}

pytorch_model.bin

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training_args.bin

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