End of training

README.md

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+---
+language:
+- ac
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- whisper-event
+- generated_from_trainer
+datasets:
+- tericlabs
+metrics:
+- wer
+model-index:
+- name: Whisper Small acholi
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Sunbird
+      type: tericlabs
+    metrics:
+    - name: Wer
+      type: wer
+      value: 121.88961646398504
+---
+
+<!-- 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 Small acholi
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sunbird dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.8028
+- Wer: 121.8896
+
+## 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: 5e-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: 1000
+- training_steps: 1000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer      |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.8441        | 3.32  | 1000 | 2.8028          | 121.8896 |
+
+
+### Framework versions
+
+- Transformers 4.38.0.dev0
+- Pytorch 2.1.0+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0