Upload README.md

README.md

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+---
+language:
+- sv
+license: apache-2.0
+tags:
+- i-dont-know-what-im-doing
+- generated_from_trainer
+datasets:
+- fimster/NST_small_whisper
+metrics:
+- wer
+model-index:
+- name: Whisper Small sv-SE NST - Lab 2
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: NST Swedish ASR
+      type: fimster/NST_small_whisper
+      config: speech
+      split: None
+      args: 'config: speech, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 10.167794316644112
+---
+
+<!-- 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 sv-SE NST - Lab 2
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the NST Swedish ASR dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1305
+- Wer: 10.1678
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.1635        | 0.67  | 1000 | 0.1694          | 13.4993 |
+| 0.07          | 1.33  | 2000 | 0.1431          | 11.3802 |
+| 0.0597        | 2.0   | 3000 | 0.1302          | 10.4682 |
+| 0.0193        | 2.67  | 4000 | 0.1305          | 10.1678 |
+
+
+### Framework versions
+
+- Transformers 4.26.0.dev0
+- Pytorch 1.13.0+cu116
+- Datasets 2.7.1
+- Tokenizers 0.13.2