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Duplicate from hypefi/my_awesome_swag_model
Browse filesCo-authored-by: Anas Boukharta <hypefi@users.noreply.huggingface.co>
- .gitattributes +34 -0
- .gitignore +1 -0
- README.md +64 -0
- config.json +26 -0
- pytorch_model.bin +3 -0
- runs/Feb08_11-19-42_6d5bcdef10d1/1675855189.4963305/events.out.tfevents.1675855189.6d5bcdef10d1.513.1 +3 -0
- runs/Feb08_11-19-42_6d5bcdef10d1/events.out.tfevents.1675855189.6d5bcdef10d1.513.0 +3 -0
- special_tokens_map.json +7 -0
- tokenizer.json +0 -0
- tokenizer_config.json +14 -0
- training_args.bin +3 -0
- vocab.txt +0 -0
.gitattributes
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checkpoint-*/
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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- swag
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metrics:
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- accuracy
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model-index:
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- name: my_awesome_swag_model
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results: []
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duplicated_from: hypefi/my_awesome_swag_model
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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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# my_awesome_swag_model
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the swag dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0107
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- Accuracy: 0.7899
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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: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: 3
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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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| 0.7454 | 1.0 | 4597 | 0.6122 | 0.7662 |
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| 0.3786 | 2.0 | 9194 | 0.6400 | 0.7833 |
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| 0.1338 | 3.0 | 13791 | 1.0107 | 0.7899 |
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### Framework versions
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- Transformers 4.26.0
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- Pytorch 1.13.1+cu116
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- Datasets 2.9.0
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- Tokenizers 0.13.2
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config.json
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{
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"_name_or_path": "bert-base-uncased",
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"architectures": [
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"BertForMultipleChoice"
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],
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"attention_probs_dropout_prob": 0.1,
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"classifier_dropout": null,
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"gradient_checkpointing": false,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "bert",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"pad_token_id": 0,
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"position_embedding_type": "absolute",
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"torch_dtype": "float32",
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"transformers_version": "4.26.0",
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"type_vocab_size": 2,
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"use_cache": true,
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"vocab_size": 30522
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}
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pytorch_model.bin
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special_tokens_map.json
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{
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tokenizer.json
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tokenizer_config.json
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training_args.bin
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vocab.txt
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