Training Completed!
Browse files- README.md +69 -0
- model.safetensors +1 -1
README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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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-base-uncased-distilled-clinc
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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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should probably proofread and complete it, then remove this comment. -->
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# distilbert-base-uncased-distilled-clinc
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2223
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- Accuracy: 0.9445
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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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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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 48
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- eval_batch_size: 48
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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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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| No log | 1.0 | 318 | 1.2786 | 0.7235 |
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| 1.5922 | 2.0 | 636 | 0.6337 | 0.8652 |
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| 1.5922 | 3.0 | 954 | 0.3711 | 0.9171 |
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| 0.5859 | 4.0 | 1272 | 0.2814 | 0.9316 |
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| 0.288 | 5.0 | 1590 | 0.2498 | 0.9381 |
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| 0.288 | 6.0 | 1908 | 0.2378 | 0.9406 |
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| 0.2186 | 7.0 | 2226 | 0.2298 | 0.9413 |
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| 0.1965 | 8.0 | 2544 | 0.2260 | 0.9435 |
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| 0.1965 | 9.0 | 2862 | 0.2234 | 0.9445 |
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| 0.1884 | 10.0 | 3180 | 0.2223 | 0.9445 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
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size 268290900
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version https://git-lfs.github.com/spec/v1
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oid sha256:4ee02bb9282cbf7d3c1708dace0fe5e1f37d9faf5cdaecb593cc57a7ee91f787
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size 268290900
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