Acc0.8764044943820225, F10.8761472718126238 , Augmented with roberta-base.csv, finetuned on google/electra-base-discriminator
Browse files- README.md +77 -0
- config.json +41 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
README.md
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---
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license: apache-2.0
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base_model: google/electra-base-discriminator
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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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- precision
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- recall
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model-index:
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- name: electra-base-discriminator_roberta-base
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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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# electra-base-discriminator_roberta-base
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This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4180
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- Accuracy: 0.8768
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- F1: 0.8767
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- Precision: 0.8766
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- Recall: 0.8768
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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: 0.0001
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- train_batch_size: 64
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- eval_batch_size: 64
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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: 1000
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- num_epochs: 25
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 0.955 | 1.0 | 91 | 0.8849 | 0.6349 | 0.5849 | 0.6173 | 0.6349 |
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| 0.4845 | 2.0 | 182 | 0.4777 | 0.8237 | 0.8221 | 0.8271 | 0.8237 |
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| 0.3434 | 3.0 | 273 | 0.3821 | 0.8580 | 0.8579 | 0.8598 | 0.8580 |
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| 0.2683 | 4.0 | 364 | 0.5158 | 0.8237 | 0.8213 | 0.8362 | 0.8237 |
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| 0.1675 | 5.0 | 455 | 0.3875 | 0.8643 | 0.8633 | 0.8651 | 0.8643 |
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| 0.1788 | 6.0 | 546 | 0.4180 | 0.8768 | 0.8767 | 0.8766 | 0.8768 |
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| 0.1669 | 7.0 | 637 | 0.4189 | 0.8768 | 0.8754 | 0.8775 | 0.8768 |
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| 0.1103 | 8.0 | 728 | 0.5338 | 0.8534 | 0.8542 | 0.8569 | 0.8534 |
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| 0.1597 | 9.0 | 819 | 0.4306 | 0.8674 | 0.8674 | 0.8676 | 0.8674 |
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| 0.1443 | 10.0 | 910 | 0.6446 | 0.8580 | 0.8574 | 0.8580 | 0.8580 |
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| 0.1012 | 11.0 | 1001 | 0.5104 | 0.8534 | 0.8535 | 0.8541 | 0.8534 |
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### Framework versions
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- Transformers 4.37.0
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- Pytorch 2.1.2
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- Datasets 2.1.0
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- Tokenizers 0.15.1
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config.json
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{
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"_name_or_path": "google/electra-base-discriminator",
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"architectures": [
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"ElectraForSequenceClassification"
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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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"embedding_size": 768,
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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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"id2label": {
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"0": "LABEL_0",
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"1": "LABEL_1",
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"2": "LABEL_2"
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},
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"LABEL_0": 0,
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"LABEL_1": 1,
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"LABEL_2": 2
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},
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"model_type": "electra",
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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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"problem_type": "single_label_classification",
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"summary_activation": "gelu",
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"summary_last_dropout": 0.1,
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"summary_type": "first",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.37.0",
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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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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:472871c948f1c03f690098da8183fa69003439fd57ed60fec35ab757b9cd23c0
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size 437962324
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:c264fc76f3c816ea1a3b1994efdbe01c8d7f60b484f2ae3be6c61fffd797b4db
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size 4664
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