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library_name: transformers
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---
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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:** [More Information Needed]
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- **Language(s) (NLP):** [More Information Needed]
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- **License:** [More Information Needed]
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- **Finetuned from model [optional]:** [More Information Needed]
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### Direct Use
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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## How to Get Started with the Model
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Use the code below to get started with the model.
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[More Information Needed]
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## Training Details
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### Training Data
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<!-- 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. -->
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[More Information Needed]
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### Training Procedure
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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#### Preprocessing [optional]
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[More Information Needed]
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#### Training Hyperparameters
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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#### Speeds, Sizes, Times [optional]
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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[More Information Needed]
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## Evaluation
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<!-- This section describes the evaluation protocols and provides the results. -->
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### Testing Data, Factors & Metrics
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#### Testing Data
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[More Information Needed]
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#### Factors
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<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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[More Information Needed]
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#### Metrics
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<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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### Results
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#### Summary
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## Model Examination [optional]
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<!-- Relevant interpretability work for the model goes here -->
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[More Information Needed]
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## Environmental Impact
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<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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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).
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- **Hardware Type:** [More Information Needed]
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- **Hours used:** [More Information Needed]
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- **Cloud Provider:** [More Information Needed]
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- **Compute Region:** [More Information Needed]
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- **Carbon Emitted:** [More Information Needed]
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## Technical Specifications [optional]
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### Model Architecture and Objective
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[More Information Needed]
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### Compute Infrastructure
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#### Hardware
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#### Software
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## Citation [optional]
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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**BibTeX:**
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[More Information Needed]
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**APA:**
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## Glossary [optional]
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[More Information Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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## Model Card Contact
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[More Information Needed]
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library_name: transformers
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base_model: Samuael/ethiopic-asr-characters
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tags:
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- generated_from_trainer
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datasets:
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- alffa_amharic
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metrics:
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- wer
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model-index:
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- name: ethiopic-asr-characters
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: alffa_amharic
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type: alffa_amharic
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config: clean
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split: None
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args: clean
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metrics:
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- name: Wer
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type: wer
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value: 0.6500682618380398
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# ethiopic-asr-characters
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This model is a fine-tuned version of [Samuael/ethiopic-asr-characters](https://huggingface.co/Samuael/ethiopic-asr-characters) on the alffa_amharic dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3111
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- Wer: 0.6501
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- Phoneme Cer: 0.1643
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer | Phoneme Cer |
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|:-------------:|:------:|:----:|:---------------:|:------:|:-----------:|
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| 3.8637 | 0.2312 | 200 | 3.7113 | 1.0 | 1.0 |
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| 3.2985 | 0.4624 | 400 | 3.1041 | 1.0 | 1.0 |
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| 3.2394 | 0.6936 | 600 | 3.0386 | 1.0 | 1.0 |
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| 3.2162 | 0.9249 | 800 | 2.9907 | 1.0 | 1.0 |
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| 2.5098 | 1.1561 | 1000 | 2.4563 | 0.9340 | 0.3008 |
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| 2.0264 | 1.3873 | 1200 | 1.7010 | 0.7740 | 0.2031 |
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| 1.4885 | 1.6185 | 1400 | 1.4274 | 0.6884 | 0.1736 |
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| 1.4836 | 1.8497 | 1600 | 1.3111 | 0.6501 | 0.1643 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.5.1+cu121
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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config.json
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{
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"_name_or_path": "Samuael/ethiopic-asr",
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"activation_dropout": 0.0,
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"adapter_attn_dim": null,
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"adapter_kernel_size": 3,
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{
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"_name_or_path": "Samuael/ethiopic-asr-characters",
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"activation_dropout": 0.0,
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"adapter_attn_dim": null,
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"adapter_kernel_size": 3,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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preprocessor_config.json
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{
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"do_normalize": true,
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"feature_extractor_type": "Wav2Vec2FeatureExtractor",
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0.0,
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"return_attention_mask": false,
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"sampling_rate": 16000
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}
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runs/Nov16_23-18-11_4286a55fbd8b/events.out.tfevents.1731800719.4286a55fbd8b.3189.0
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runs/Nov17_05-08-36_4286a55fbd8b/events.out.tfevents.1731821738.4286a55fbd8b.3189.1
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training_args.bin
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