End of training

README.md

@@ -0,0 +1,82 @@
+---
+library_name: transformers
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-large-v3
+tags:
+- generated_from_trainer
+datasets:
+- stillerman/libristutter-4.7k
+metrics:
+- wer
+model-index:
+- name: Whisper Large V3 Stutter - Ariel Cerda
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Libristutter 4.7k
+      type: stillerman/libristutter-4.7k
+      args: 'config: en, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 19.625834127740703
+---
+
+<!-- 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 Stutter - Ariel Cerda
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Libristutter 4.7k dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4927
+- Wer: 19.6258
+
+## 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: 5000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Wer     |
+|:-------------:|:-------:|:----:|:---------------:|:-------:|
+| 0.0358        | 3.7453  | 1000 | 0.2987          | 17.1711 |
+| 0.0027        | 7.4906  | 2000 | 0.3993          | 18.0231 |
+| 0.0004        | 11.2360 | 3000 | 0.4394          | 19.9476 |
+| 0.0002        | 14.9813 | 4000 | 0.4826          | 20.0786 |
+| 0.0001        | 18.7266 | 5000 | 0.4927          | 19.6258 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.1
+- Tokenizers 0.19.1

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+}

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