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README.md
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---
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library_name: transformers
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language:
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- en
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base_model: gokulsrinivasagan/bert_base_lda_100_v1
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tags:
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- generated_from_trainer
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datasets:
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- glue
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metrics:
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- accuracy
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- f1
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model-index:
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- name: bert_base_lda_100_v1_qqp
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: GLUE QQP
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type: glue
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args: qqp
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.6318327974276527
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- name: F1
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type: f1
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value: 0.0
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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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# bert_base_lda_100_v1_qqp
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This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_100_v1) on
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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- F1: 0.
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- Combined Score: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 256
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- eval_batch_size: 256
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- seed: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1
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| 0.6586 | 9.0 | 12798 | 0.6578 | 0.6318 | 0.0 | 0.3159 |
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| 0.6586 | 10.0 | 14220 | 0.6578 | 0.6318 | 0.0 | 0.3159 |
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| 0.6585 | 11.0 | 15642 | 0.6578 | 0.6318 | 0.0 | 0.3159 |
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| 0.6585 | 12.0 | 17064 | 0.6576 | 0.6318 | 0.0 | 0.3159 |
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### Framework versions
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library_name: transformers
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base_model: gokulsrinivasagan/bert_base_lda_100_v1
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: bert_base_lda_100_v1_qqp
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results: []
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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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# bert_base_lda_100_v1_qqp
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This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_100_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_100_v1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4346
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- Accuracy: 0.8693
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- F1: 0.8285
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- Combined Score: 0.8489
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 256
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- eval_batch_size: 256
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- seed: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
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| 0.4474 | 1.0 | 1422 | 0.3685 | 0.8284 | 0.7614 | 0.7949 |
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| 0.3271 | 2.0 | 2844 | 0.3386 | 0.8476 | 0.8103 | 0.8290 |
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| 0.2564 | 3.0 | 4266 | 0.3234 | 0.8609 | 0.8186 | 0.8398 |
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| 0.1978 | 4.0 | 5688 | 0.3628 | 0.8653 | 0.8263 | 0.8458 |
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| 0.1516 | 5.0 | 7110 | 0.4014 | 0.8695 | 0.8253 | 0.8474 |
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| 0.1169 | 6.0 | 8532 | 0.3964 | 0.8673 | 0.8278 | 0.8475 |
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| 0.093 | 7.0 | 9954 | 0.4813 | 0.8676 | 0.8279 | 0.8478 |
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| 0.076 | 8.0 | 11376 | 0.4346 | 0.8693 | 0.8285 | 0.8489 |
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### Framework versions
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model.safetensors
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size 437953248
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size 437953248
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