End of training

README.md

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+---
+language:
+- en
+license: apache-2.0
+base_model: futureProofGlitch/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- speechcolab/gigaspeech
+metrics:
+- wer
+model-index:
+- name: FutureProofGlitch - Whisper Small - Version 2.0
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Gigaspeech
+      type: speechcolab/gigaspeech
+      config: xs
+      split: test
+      args: xs
+    metrics:
+    - name: Wer
+      type: wer
+      value: 59.27575494338845
+---
+
+<!-- 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. -->
+
+# FutureProofGlitch - Whisper Small - Version 2.0
+
+This model is a fine-tuned version of [futureProofGlitch/whisper-small](https://huggingface.co/futureProofGlitch/whisper-small) on the Gigaspeech dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.1812
+- Wer Ortho: 65.1852
+- Wer: 59.2758
+
+## 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: 1.5e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: constant_with_warmup
+- lr_scheduler_warmup_steps: 50
+- training_steps: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
+| 1.6925        | 0.5   | 500  | 1.1812          | 65.1852   | 59.2758 |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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+}