End of training

README.md

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+---
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- Jzuluaga/atcosim_corpus
+metrics:
+- wer
+model-index:
+- name: Whisper Base ATCOSIM
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: atcosim_corpus_numbers_converted
+      type: Jzuluaga/atcosim_corpus
+      args: 'config: en, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 404.9337012855893
+---
+
+<!-- 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 ATCOSIM
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the atcosim_corpus_numbers_converted dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5964
+- Wer: 404.9337
+
+## 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: 1000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer      |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 8.7316        | 0.2092 | 100  | 8.1521          | 110.7020 |
+| 5.3768        | 0.4184 | 200  | 5.2758          | 110.9713 |
+| 3.2842        | 0.6276 | 300  | 3.4243          | 119.1492 |
+| 1.892         | 0.8368 | 400  | 2.1743          | 121.4377 |
+| 0.9999        | 1.0460 | 500  | 1.4513          | 168.8160 |
+| 0.6472        | 1.2552 | 600  | 1.0157          | 369.7449 |
+| 0.529         | 1.4644 | 700  | 0.8372          | 356.8554 |
+| 0.4086        | 1.6736 | 800  | 0.6973          | 300.4644 |
+| 0.3559        | 1.8828 | 900  | 0.6164          | 361.0150 |
+| 0.2302        | 2.0921 | 1000 | 0.5964          | 404.9337 |
+
+
+### Framework versions
+
+- Transformers 4.42.0.dev0
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

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+}

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