End of training

README.md

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+---
+library_name: transformers
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-large
+tags:
+- generated_from_trainer
+datasets:
+- Jzuluaga/atcosim_corpus
+metrics:
+- wer
+model-index:
+- name: Whisper Large - Whisper with atcosim_corpus
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: The ATCOSIM Air Traffic Control Simulation Speech corpus is a speech database
+        of air traffic control (ATC) operator speech, provided by Graz University
+        of Technology (TUG) and Eurocontrol Experimental Centre (EEC)
+      type: Jzuluaga/atcosim_corpus
+      args: 'config: en, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.9495627594735447
+---
+
+<!-- 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 - Whisper with atcosim_corpus
+
+This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the The ATCOSIM Air Traffic Control Simulation Speech corpus is a speech database of air traffic control (ATC) operator speech, provided by Graz University of Technology (TUG) and Eurocontrol Experimental Centre (EEC) dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0413
+- Wer: 0.9496
+
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 500
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer    |
+|:-------------:|:------:|:----:|:---------------:|:------:|
+| 0.012         | 2.0921 | 1000 | 0.0405          | 1.2543 |
+| 0.0019        | 4.1841 | 2000 | 0.0372          | 1.0776 |
+| 0.0001        | 6.2762 | 3000 | 0.0407          | 0.9716 |
+| 0.0           | 8.3682 | 4000 | 0.0413          | 0.9496 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

generation_config.json

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+  "is_multilingual": true,
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+  "transformers_version": "4.44.2"
+}