gokulsrinivasagan
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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/distilbert_lda_5_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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model-index:
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- name: distilbert_lda_5_v1_qnli
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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 QNLI
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type: glue
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args: qnli
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.5053999633900788
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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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# distilbert_lda_5_v1_qnli
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This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_5_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_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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## 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 Loss | Epoch | Step | Validation Loss | Accuracy |
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| 0.693 | 8.0 | 3280 | 0.6934 | 0.4946 |
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| 0.6932 | 9.0 | 3690 | 0.6933 | 0.5054 |
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| 0.6932 | 10.0 | 4100 | 0.6934 | 0.4946 |
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| 0.6932 | 11.0 | 4510 | 0.6933 | 0.5054 |
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| 0.6932 | 12.0 | 4920 | 0.6934 | 0.4946 |
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### Framework versions
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---
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library_name: transformers
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base_model: gokulsrinivasagan/distilbert_lda_5_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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model-index:
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- name: distilbert_lda_5_v1_qnli
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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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# distilbert_lda_5_v1_qnli
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This model is a fine-tuned version of [gokulsrinivasagan/distilbert_lda_5_v1](https://huggingface.co/gokulsrinivasagan/distilbert_lda_5_v1) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6610
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- Accuracy: 0.8122
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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 Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.497 | 1.0 | 410 | 0.3871 | 0.8303 |
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| 0.3635 | 2.0 | 820 | 0.3706 | 0.8435 |
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| 0.2745 | 3.0 | 1230 | 0.3750 | 0.8376 |
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| 0.1968 | 4.0 | 1640 | 0.4567 | 0.8309 |
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| 0.1394 | 5.0 | 2050 | 0.5239 | 0.8321 |
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| 0.1001 | 6.0 | 2460 | 0.5522 | 0.8342 |
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| 0.0764 | 7.0 | 2870 | 0.6610 | 0.8122 |
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### Framework versions
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model.safetensors
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