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  2. config.json +110 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +9 -0
  5. training_args.bin +3 -0
README.md CHANGED
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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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-
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- <!-- Provide a quick summary of what the model is/does. -->
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-
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- ## Model Details
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-
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- ### Model Description
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-
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- <!-- Provide a longer summary of what this model is. -->
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-
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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-
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- - **Developed by:** [More Information Needed]
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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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-
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- ### Model Sources [optional]
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-
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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-
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- ## Uses
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-
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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-
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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-
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- ### Downstream Use [optional]
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-
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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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-
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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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-
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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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-
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- ## How to Get Started with the Model
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-
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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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-
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- ## Training Details
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-
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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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- <!-- This should link to a Dataset Card if possible. -->
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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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- [More Information Needed]
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- ### Results
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- [More Information Needed]
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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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- ## Glossary [optional]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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-
 
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  ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-base-960h
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - audiofolder
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: JP-base-clean-0215
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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: audiofolder
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+ type: audiofolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.983
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  ---
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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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+
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+ # JP-base-clean-0215
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the audiofolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0988
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+ - Wer: 0.983
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_steps: 3125.0
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:-----:|
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+ | 5.5004 | 1.0 | 625 | 7.2647 | 1.0 |
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+ | 4.0716 | 2.0 | 1250 | 4.3871 | 1.0 |
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+ | 3.3302 | 3.0 | 1875 | 3.1038 | 1.0 |
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+ | 0.8423 | 4.0 | 2500 | 0.9833 | 0.998 |
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+ | 0.5152 | 5.0 | 3125 | 0.7318 | 0.996 |
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+ | 0.3984 | 6.0 | 3750 | 0.4784 | 0.996 |
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+ | 0.3481 | 7.0 | 4375 | 0.3688 | 0.994 |
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+ | 0.3149 | 8.0 | 5000 | 0.3821 | 0.994 |
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+ | 0.2852 | 9.0 | 5625 | 0.2320 | 0.992 |
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+ | 0.2576 | 10.0 | 6250 | 0.2887 | 0.991 |
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+ | 0.2423 | 11.0 | 6875 | 0.2071 | 0.991 |
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+ | 0.2278 | 12.0 | 7500 | 0.1700 | 0.989 |
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+ | 0.2104 | 13.0 | 8125 | 0.1553 | 0.991 |
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+ | 0.2016 | 14.0 | 8750 | 0.1500 | 0.988 |
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+ | 0.1967 | 15.0 | 9375 | 0.1357 | 0.985 |
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+ | 0.1838 | 16.0 | 10000 | 0.1615 | 0.988 |
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+ | 0.172 | 17.0 | 10625 | 0.1238 | 0.986 |
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+ | 0.1687 | 18.0 | 11250 | 0.1270 | 0.988 |
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+ | 0.1555 | 19.0 | 11875 | 0.1221 | 0.987 |
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+ | 0.1532 | 20.0 | 12500 | 0.1168 | 0.988 |
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+ | 0.1414 | 21.0 | 13125 | 0.1175 | 0.988 |
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+ | 0.1366 | 22.0 | 13750 | 0.1231 | 0.985 |
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+ | 0.1341 | 23.0 | 14375 | 0.1004 | 0.987 |
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+ | 0.1273 | 24.0 | 15000 | 0.1175 | 0.984 |
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+ | 0.1199 | 25.0 | 15625 | 0.1246 | 0.984 |
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+ | 0.1181 | 26.0 | 16250 | 0.1382 | 0.985 |
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+ | 0.1152 | 27.0 | 16875 | 0.1064 | 0.984 |
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+ | 0.1116 | 28.0 | 17500 | 0.1075 | 0.985 |
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+ | 0.1097 | 29.0 | 18125 | 0.1110 | 0.986 |
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+ | 0.1074 | 30.0 | 18750 | 0.1399 | 0.983 |
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+ | 0.0997 | 31.0 | 19375 | 0.1385 | 0.983 |
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+ | 0.0998 | 32.0 | 20000 | 0.1185 | 0.983 |
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+ | 0.0973 | 33.0 | 20625 | 0.1491 | 0.982 |
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+ | 0.0988 | 34.0 | 21250 | 0.1232 | 0.983 |
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+ | 0.0942 | 35.0 | 21875 | 0.1205 | 0.98 |
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+ | 0.0949 | 36.0 | 22500 | 0.1109 | 0.981 |
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+ | 0.0947 | 37.0 | 23125 | 0.1119 | 0.982 |
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+ | 0.0939 | 38.0 | 23750 | 0.1151 | 0.983 |
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+ | 0.0876 | 39.0 | 24375 | 0.1001 | 0.982 |
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+ | 0.0893 | 40.0 | 25000 | 0.0957 | 0.984 |
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+ | 0.0897 | 41.0 | 25625 | 0.0924 | 0.982 |
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+ | 0.0859 | 42.0 | 26250 | 0.0959 | 0.983 |
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+ | 0.0881 | 43.0 | 26875 | 0.0996 | 0.983 |
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+ | 0.0885 | 44.0 | 27500 | 0.0972 | 0.982 |
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+ | 0.0871 | 45.0 | 28125 | 0.0984 | 0.983 |
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+ | 0.0866 | 46.0 | 28750 | 0.0976 | 0.983 |
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+ | 0.0858 | 47.0 | 29375 | 0.0982 | 0.983 |
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+ | 0.0882 | 48.0 | 30000 | 0.0982 | 0.983 |
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+ | 0.0848 | 49.0 | 30625 | 0.0988 | 0.983 |
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+ | 0.0855 | 50.0 | 31250 | 0.0988 | 0.983 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.37.2
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+ - Pytorch 2.2.0
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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