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wav2vec2-turkish-300m-2

Automatic Speech Recognition
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wav2vec2
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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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- ### 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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- ### Direct Use
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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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- ## Training Details
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- ### Training Data
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- ### Training Procedure
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- #### Preprocessing [optional]
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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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- ## 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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- 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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-
 
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  ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-xls-r-300m
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - common_voice_16_1
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-turkish-300m-2
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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_16_1
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+ type: common_voice_16_1
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+ config: tr
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+ split: test
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+ args: tr
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.27864667601481324
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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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+ # wav2vec2-turkish-300m-2
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_16_1 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3293
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+ - Wer: 0.2786
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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: 0.0003
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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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: linear
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+ - lr_scheduler_warmup_steps: 0.1
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+ - num_epochs: 20
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+ - mixed_precision_training: Native AMP
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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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+ | 2.234 | 0.1461 | 400 | 0.7428 | 0.7198 |
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+ | 0.6888 | 0.2922 | 800 | 0.7178 | 0.7417 |
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+ | 0.5978 | 0.4383 | 1200 | 0.5479 | 0.6138 |
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+ | 0.5608 | 0.5844 | 1600 | 0.5362 | 0.5827 |
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+ | 0.52 | 0.7305 | 2000 | 0.6510 | 0.6688 |
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+ | 0.5019 | 0.8766 | 2400 | 0.5023 | 0.5676 |
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+ | 0.4791 | 1.0226 | 2800 | 0.4218 | 0.5065 |
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+ | 0.4217 | 1.1687 | 3200 | 0.4133 | 0.4860 |
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+ | 0.416 | 1.3148 | 3600 | 0.4329 | 0.4964 |
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+ | 0.4067 | 1.4609 | 4000 | 0.4084 | 0.4871 |
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+ | 0.4046 | 1.6070 | 4400 | 0.4238 | 0.5113 |
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+ | 0.4108 | 1.7531 | 4800 | 0.4063 | 0.4854 |
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+ | 0.4018 | 1.8992 | 5200 | 0.4123 | 0.4861 |
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+ | 0.3878 | 2.0453 | 5600 | 0.3969 | 0.4763 |
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+ | 0.351 | 2.1914 | 6000 | 0.4012 | 0.4690 |
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+ | 0.3454 | 2.3375 | 6400 | 0.4011 | 0.4741 |
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+ | 0.3487 | 2.4836 | 6800 | 0.3908 | 0.4816 |
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+ | 0.3417 | 2.6297 | 7200 | 0.3884 | 0.4578 |
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+ | 0.3408 | 2.7757 | 7600 | 0.4002 | 0.4674 |
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+ | 0.3374 | 2.9218 | 8000 | 0.3914 | 0.4524 |
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+ | 0.3121 | 3.0679 | 8400 | 0.4217 | 0.4763 |
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+ | 0.3025 | 3.2140 | 8800 | 0.3905 | 0.4598 |
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+ | 0.3016 | 3.3601 | 9200 | 0.3831 | 0.4505 |
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+ | 0.2974 | 3.5062 | 9600 | 0.3948 | 0.4568 |
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+ | 0.3032 | 3.6523 | 10000 | 0.3888 | 0.4512 |
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+ | 0.2929 | 3.7984 | 10400 | 0.3900 | 0.4461 |
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+ | 0.2922 | 3.9445 | 10800 | 0.3846 | 0.4540 |
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+ | 0.2745 | 4.0906 | 11200 | 0.3748 | 0.4374 |
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+ | 0.2665 | 4.2367 | 11600 | 0.3993 | 0.4336 |
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+ | 0.2696 | 4.3828 | 12000 | 0.3657 | 0.4333 |
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+ | 0.2622 | 4.5289 | 12400 | 0.3628 | 0.4341 |
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+ | 0.2585 | 4.6749 | 12800 | 0.3802 | 0.4288 |
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+ | 0.2604 | 4.8210 | 13200 | 0.3604 | 0.4236 |
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+ | 0.2575 | 4.9671 | 13600 | 0.3650 | 0.4322 |
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+ | 0.2313 | 5.1132 | 14000 | 0.3521 | 0.4021 |
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+ | 0.2323 | 5.2593 | 14400 | 0.3513 | 0.4009 |
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+ | 0.2351 | 5.4054 | 14800 | 0.3265 | 0.3963 |
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+ | 0.2229 | 5.5515 | 15200 | 0.3523 | 0.3978 |
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+ | 0.234 | 5.6976 | 15600 | 0.3375 | 0.3931 |
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+ | 0.229 | 5.8437 | 16000 | 0.3380 | 0.3945 |
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+ | 0.2313 | 5.9898 | 16400 | 0.3403 | 0.3957 |
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+ | 0.2069 | 6.1359 | 16800 | 0.3522 | 0.3979 |
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+ | 0.2162 | 6.2820 | 17200 | 0.3685 | 0.4061 |
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+ | 0.2144 | 6.4280 | 17600 | 0.3308 | 0.3878 |
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+ | 0.2115 | 6.5741 | 18000 | 0.3530 | 0.3974 |
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+ | 0.2108 | 6.7202 | 18400 | 0.3191 | 0.3802 |
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+ | 0.2107 | 6.8663 | 18800 | 0.3313 | 0.3818 |
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+ | 0.1977 | 7.0124 | 19200 | 0.3454 | 0.3807 |
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+ | 0.1903 | 7.1585 | 19600 | 0.3386 | 0.3785 |
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+ | 0.1924 | 7.3046 | 20000 | 0.3369 | 0.3841 |
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+ | 0.1912 | 7.4507 | 20400 | 0.3385 | 0.3782 |
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+ | 0.1879 | 7.5968 | 20800 | 0.3302 | 0.3728 |
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+ | 0.1903 | 7.7429 | 21200 | 0.3254 | 0.3636 |
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+ | 0.1828 | 7.8890 | 21600 | 0.3499 | 0.3723 |
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+ | 0.1803 | 8.0351 | 22000 | 0.3371 | 0.3834 |
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+ | 0.1711 | 8.1812 | 22400 | 0.3498 | 0.3879 |
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+ | 0.169 | 8.3272 | 22800 | 0.3332 | 0.3731 |
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+ | 0.1657 | 8.4733 | 23200 | 0.3223 | 0.3665 |
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+ | 0.1682 | 8.6194 | 23600 | 0.3386 | 0.3696 |
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+ | 0.1732 | 8.7655 | 24000 | 0.3564 | 0.3726 |
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+ | 0.1723 | 8.9116 | 24400 | 0.3336 | 0.3685 |
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+ | 0.1681 | 9.0577 | 24800 | 0.3328 | 0.3543 |
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+ | 0.1547 | 9.2038 | 25200 | 0.3358 | 0.3533 |
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+ | 0.1572 | 9.3499 | 25600 | 0.3088 | 0.3563 |
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+ | 0.1518 | 9.4960 | 26000 | 0.3219 | 0.3513 |
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+ | 0.1532 | 9.6421 | 26400 | 0.3060 | 0.3491 |
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+ | 0.154 | 9.7882 | 26800 | 0.3091 | 0.3457 |
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+ | 0.1478 | 9.9343 | 27200 | 0.3159 | 0.3401 |
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+ | 0.1499 | 10.0804 | 27600 | 0.3219 | 0.3485 |
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+ | 0.1337 | 10.2264 | 28000 | 0.3109 | 0.3443 |
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+ | 0.1364 | 10.3725 | 28400 | 0.3281 | 0.3456 |
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+ | 0.1329 | 10.5186 | 28800 | 0.3143 | 0.3408 |
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+ | 0.146 | 10.6647 | 29200 | 0.3285 | 0.3383 |
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+ | 0.1403 | 10.8108 | 29600 | 0.3180 | 0.3387 |
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+ | 0.14 | 10.9569 | 30000 | 0.3086 | 0.3350 |
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+ | 0.1258 | 11.1030 | 30400 | 0.3253 | 0.3345 |
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+ | 0.1229 | 11.2491 | 30800 | 0.3236 | 0.3392 |
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+ | 0.1241 | 11.3952 | 31200 | 0.3257 | 0.3349 |
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+ | 0.1224 | 11.5413 | 31600 | 0.3260 | 0.3287 |
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+ | 0.1218 | 11.6874 | 32000 | 0.3153 | 0.3330 |
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+ | 0.1267 | 11.8335 | 32400 | 0.3141 | 0.3298 |
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+ | 0.1246 | 11.9795 | 32800 | 0.3144 | 0.3281 |
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+ | 0.113 | 12.1256 | 33200 | 0.3415 | 0.3367 |
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+ | 0.1121 | 12.2717 | 33600 | 0.3262 | 0.3294 |
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+ | 0.1147 | 12.4178 | 34000 | 0.3378 | 0.3287 |
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+ | 0.114 | 12.5639 | 34400 | 0.3121 | 0.3240 |
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+ | 0.1054 | 12.7100 | 34800 | 0.3288 | 0.3199 |
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+ | 0.1081 | 12.8561 | 35200 | 0.3010 | 0.3220 |
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+ | 0.1137 | 13.0022 | 35600 | 0.3261 | 0.3229 |
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+ | 0.102 | 13.1483 | 36000 | 0.3168 | 0.3177 |
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+ | 0.1 | 13.2944 | 36400 | 0.3224 | 0.3173 |
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+ | 0.1003 | 13.4405 | 36800 | 0.3175 | 0.3205 |
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+ | 0.098 | 13.5866 | 37200 | 0.3021 | 0.3158 |
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+ | 0.0974 | 13.7327 | 37600 | 0.3057 | 0.3154 |
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+ | 0.0952 | 13.8787 | 38000 | 0.3257 | 0.3155 |
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+ | 0.095 | 14.0248 | 38400 | 0.3229 | 0.3097 |
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+ | 0.0902 | 14.1709 | 38800 | 0.3285 | 0.3152 |
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+ | 0.0917 | 14.3170 | 39200 | 0.3279 | 0.3160 |
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+ | 0.0905 | 14.4631 | 39600 | 0.3278 | 0.3111 |
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+ | 0.092 | 14.6092 | 40000 | 0.3209 | 0.3105 |
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+ | 0.0862 | 14.7553 | 40400 | 0.3109 | 0.3064 |
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+ | 0.0912 | 14.9014 | 40800 | 0.3116 | 0.3056 |
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+ | 0.086 | 15.0475 | 41200 | 0.3383 | 0.3038 |
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+ | 0.0832 | 15.1936 | 41600 | 0.3189 | 0.3018 |
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+ | 0.0773 | 15.3397 | 42000 | 0.3150 | 0.3033 |
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+ | 0.0817 | 15.4858 | 42400 | 0.3253 | 0.3040 |
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+ | 0.0775 | 15.6318 | 42800 | 0.3223 | 0.3030 |
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+ | 0.0767 | 15.7779 | 43200 | 0.3225 | 0.2970 |
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+ | 0.0796 | 15.9240 | 43600 | 0.3368 | 0.3047 |
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+ | 0.0763 | 16.0701 | 44000 | 0.3252 | 0.2971 |
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+ | 0.075 | 16.2162 | 44400 | 0.3188 | 0.3002 |
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+ | 0.0744 | 16.3623 | 44800 | 0.3207 | 0.2947 |
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+ | 0.0729 | 16.5084 | 45200 | 0.3214 | 0.2956 |
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+ | 0.0732 | 16.6545 | 45600 | 0.3278 | 0.2927 |
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+ | 0.0694 | 16.8006 | 46000 | 0.3364 | 0.2924 |
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+ | 0.0753 | 16.9467 | 46400 | 0.3263 | 0.2881 |
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+ | 0.072 | 17.0928 | 46800 | 0.3317 | 0.2909 |
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+ | 0.0658 | 17.2389 | 47200 | 0.3376 | 0.2902 |
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+ | 0.07 | 17.3850 | 47600 | 0.3282 | 0.2902 |
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+ | 0.0636 | 17.5310 | 48000 | 0.3321 | 0.2920 |
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+ | 0.0655 | 17.6771 | 48400 | 0.3274 | 0.2884 |
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+ | 0.0623 | 17.8232 | 48800 | 0.3316 | 0.2890 |
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+ | 0.0621 | 17.9693 | 49200 | 0.3209 | 0.2872 |
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+ | 0.0637 | 18.1154 | 49600 | 0.3281 | 0.2830 |
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+ | 0.0616 | 18.2615 | 50000 | 0.3393 | 0.2852 |
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+ | 0.0605 | 18.4076 | 50400 | 0.3371 | 0.2849 |
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+ | 0.0614 | 18.5537 | 50800 | 0.3277 | 0.2836 |
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+ | 0.0571 | 18.6998 | 51200 | 0.3317 | 0.2821 |
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+ | 0.0555 | 18.8459 | 51600 | 0.3364 | 0.2816 |
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+ | 0.061 | 18.9920 | 52000 | 0.3251 | 0.2797 |
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+ | 0.0571 | 19.1381 | 52400 | 0.3343 | 0.2811 |
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+ | 0.0614 | 19.2841 | 52800 | 0.3300 | 0.2810 |
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+ | 0.0534 | 19.4302 | 53200 | 0.3324 | 0.2795 |
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+ | 0.0562 | 19.5763 | 53600 | 0.3322 | 0.2789 |
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+ | 0.0545 | 19.7224 | 54000 | 0.3310 | 0.2789 |
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+ | 0.0596 | 19.8685 | 54400 | 0.3293 | 0.2786 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.2+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
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