Update README.md

README.md

@@ -1,199 +1,73 @@
 ---
-library_name: transformers
-tags: []
+license: agpl-3.0
+metrics:
+- wer
+base_model:
+- openai/whisper-large-v3-turbo
+pipeline_tag: automatic-speech-recognition
+tags:
+- upper_sorbian
 ---
 
-# Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+## Model Description
 
+This model was fine-tuned on over 24 hours of transcribed upper sorbian speech to aid future research, conservation and revitalisation of the language.
 
 
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
+## Training Data
+- **Source:** Stiftung für das sorbische Volk / Załožba za serbski lud (https://stiftung.sorben.com/)
+- **Volume:** 1493 Minutes, 10% Validation Set, 10% Test Set
 
 ## Training Details
+- **Hyperparameters**: 
+  - Batch size: 64
+  - Learning rate: 3e-6, linear decay
+- **Optimizer**: AdamW
+- **Warmup**: 1000 steps
+- **Additional Techniques**: BF16 training, initial 15 layers frozen
 
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
 
-## Evaluation
+## Performance
+### Metrics
+- **Word Error Rate:** 6.2
 
-<!-- This section describes the evaluation protocols and provides the results. -->
+## Usage
+### Example Code
 
-### Testing Data, Factors & Metrics
+To use the model, follow this example code:
 
-#### Testing Data
+```python
+import torch
+import torchaudio
+from transformers import WhisperProcessor, WhisperForConditionalGeneration
 
-<!-- This should link to a Dataset Card if possible. -->
+# Load the model and processor
+model_name = "DILHTWD/whisper-large-v3-turbo-hsb"
+processor_name = "openai/whisper-large-v3-turbo"
+processor = WhisperProcessor.from_pretrained(processor_name)
+model = WhisperForConditionalGeneration.from_pretrained(model_name)
 
-[More Information Needed]
+# Load and preprocess the audio
+audio, sample_rate = torchaudio.load("test.mp3")
+if sample_rate != 16000:
+    audio = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=16000)(audio)
+input_features = processor(audio.squeeze().numpy(), sampling_rate=16000, return_tensors="pt").input_features
 
-#### Factors
+# Generate transcription
+with torch.no_grad():
+    predicted_ids = model.generate(input_features)
+    transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+# Print the transcription
+print("Transcription:", transcription)
+```
 
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+## Model Details
+- **Model Name:** DILHTWD/whisper-large-v3-turbo-hsb
+- **Publisher:** Data Intelligence Lab, Hochschule für Technik und Wirtschaft Dresden
+- **Model Version:** 1.0.0
+- **Model Date:** 2024-11-15
+- **License:** [AGPL-3.0](https://www.gnu.org/licenses/agpl-3.0.de.html)
+- **Architecture:** Whisper Large v3 Turbo
+- **Task:** Automatic Speech Recognition