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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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- <!-- Provide a quick summary of what the model is/does. -->
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- ## Model Details
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- ### Model Description
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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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- ## Uses
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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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- ### Direct Use
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- ### Downstream Use [optional]
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- ## Bias, Risks, and Limitations
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- ### Recommendations
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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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- ### 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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- ## Evaluation
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- ### Testing Data, Factors & Metrics
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- #### Factors
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- #### Metrics
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- ## Environmental Impact
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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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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- ## Glossary [optional]
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- [More Information Needed]
 
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  ---
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  library_name: transformers
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+ license: mit
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+ base_model: facebook/w2v-bert-2.0
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_17_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: w2v-bert-grain-lg_cv_only_v2
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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: common_voice_17_0
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+ type: common_voice_17_0
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+ config: lg
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+ split: test[:10%]
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+ args: lg
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.2319647170009451
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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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+ # w2v-bert-grain-lg_cv_only_v2
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+
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+ This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.6384
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+ - Wer: 0.2320
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+ - Cer: 0.0721
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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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+ More information needed
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 8
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+ - eval_batch_size: 4
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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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+ - num_epochs: 80
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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+ |:-------------:|:-----:|:------:|:---------------:|:------:|:------:|
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+ | 0.3102 | 1.0 | 8884 | 0.4540 | 0.3644 | 0.1028 |
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+ | 0.2032 | 2.0 | 17768 | 0.3881 | 0.3005 | 0.0845 |
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+ | 0.1687 | 3.0 | 26652 | 0.4061 | 0.3139 | 0.0883 |
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+ | 0.148 | 4.0 | 35536 | 0.4048 | 0.2879 | 0.0825 |
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+ | 0.1327 | 5.0 | 44420 | 0.4136 | 0.2860 | 0.0831 |
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+ | 0.1191 | 6.0 | 53304 | 0.3685 | 0.2889 | 0.0843 |
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+ | 0.1087 | 7.0 | 62188 | 0.4108 | 0.2630 | 0.0810 |
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+ | 0.0996 | 8.0 | 71072 | 0.3682 | 0.2628 | 0.0789 |
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+ | 0.0918 | 9.0 | 79956 | 0.4126 | 0.2672 | 0.0779 |
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+ | 0.0854 | 10.0 | 88840 | 0.3482 | 0.2628 | 0.0783 |
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+ | 0.0778 | 11.0 | 97724 | 0.3948 | 0.2540 | 0.0773 |
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+ | 0.0719 | 12.0 | 106608 | 0.3530 | 0.2477 | 0.0740 |
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+ | 0.066 | 13.0 | 115492 | 0.4267 | 0.2604 | 0.0785 |
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+ | 0.0595 | 14.0 | 124376 | 0.3779 | 0.2467 | 0.0727 |
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+ | 0.0541 | 15.0 | 133260 | 0.4424 | 0.2622 | 0.0813 |
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+ | 0.0485 | 16.0 | 142144 | 0.3848 | 0.2500 | 0.0755 |
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+ | 0.044 | 17.0 | 151028 | 0.3752 | 0.2465 | 0.0736 |
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+ | 0.0391 | 18.0 | 159912 | 0.3722 | 0.2524 | 0.0753 |
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+ | 0.0347 | 19.0 | 168796 | 0.4386 | 0.2481 | 0.0762 |
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+ | 0.0309 | 20.0 | 177680 | 0.4647 | 0.2552 | 0.0788 |
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+ | 0.0273 | 21.0 | 186564 | 0.4453 | 0.2468 | 0.0736 |
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+ | 0.0252 | 22.0 | 195448 | 0.4612 | 0.2450 | 0.0750 |
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+ | 0.0229 | 23.0 | 204332 | 0.4624 | 0.2510 | 0.0750 |
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+ | 0.0209 | 24.0 | 213216 | 0.4640 | 0.2535 | 0.0739 |
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+ | 0.0186 | 25.0 | 222100 | 0.4309 | 0.2542 | 0.0747 |
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+ | 0.0173 | 26.0 | 230984 | 0.4339 | 0.2490 | 0.0734 |
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+ | 0.016 | 27.0 | 239868 | 0.4463 | 0.2477 | 0.0740 |
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+ | 0.0143 | 28.0 | 248752 | 0.5788 | 0.2432 | 0.0784 |
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+ | 0.0135 | 29.0 | 257636 | 0.4962 | 0.2482 | 0.0745 |
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+ | 0.0124 | 30.0 | 266520 | 0.5620 | 0.2448 | 0.0794 |
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+ | 0.0116 | 31.0 | 275404 | 0.5030 | 0.2419 | 0.0749 |
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+ | 0.0108 | 32.0 | 284288 | 0.4731 | 0.2374 | 0.0729 |
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+ | 0.0099 | 33.0 | 293172 | 0.4890 | 0.2425 | 0.0736 |
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+ | 0.0095 | 34.0 | 302056 | 0.5449 | 0.2449 | 0.0783 |
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+ | 0.0086 | 35.0 | 310940 | 0.5007 | 0.2355 | 0.0726 |
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+ | 0.0082 | 36.0 | 319824 | 0.4715 | 0.2372 | 0.0738 |
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+ | 0.0079 | 37.0 | 328708 | 0.5407 | 0.2430 | 0.0731 |
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+ | 0.0072 | 38.0 | 337592 | 0.5361 | 0.2374 | 0.0738 |
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+ | 0.0068 | 39.0 | 346476 | 0.5152 | 0.2459 | 0.0755 |
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+ | 0.0063 | 40.0 | 355360 | 0.4737 | 0.2316 | 0.0715 |
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+ | 0.0058 | 41.0 | 364244 | 0.5980 | 0.2391 | 0.0779 |
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+ | 0.0052 | 42.0 | 373128 | 0.5633 | 0.2360 | 0.0727 |
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+ | 0.0051 | 43.0 | 382012 | 0.5640 | 0.2352 | 0.0732 |
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+ | 0.0046 | 44.0 | 390896 | 0.5674 | 0.2270 | 0.0710 |
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+ | 0.0044 | 45.0 | 399780 | 0.5487 | 0.2352 | 0.0717 |
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+ | 0.0042 | 46.0 | 408664 | 0.6279 | 0.2436 | 0.0786 |
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+ | 0.0039 | 47.0 | 417548 | 0.6260 | 0.2438 | 0.0770 |
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+ | 0.0038 | 48.0 | 426432 | 0.5995 | 0.2328 | 0.0763 |
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+ | 0.0036 | 49.0 | 435316 | 0.6540 | 0.2403 | 0.0776 |
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+ | 0.0031 | 50.0 | 444200 | 0.5347 | 0.2370 | 0.0747 |
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+ | 0.0028 | 51.0 | 453084 | 0.6086 | 0.2490 | 0.0739 |
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+ | 0.0026 | 52.0 | 461968 | 0.5515 | 0.2287 | 0.0693 |
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+ | 0.0025 | 53.0 | 470852 | 0.6788 | 0.2414 | 0.0793 |
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+ | 0.0023 | 54.0 | 479736 | 0.6384 | 0.2320 | 0.0721 |
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.1
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+ - Pytorch 2.1.0+cu118
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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