SeyedAli/Persian-Text-Emotion-Bert-LORA
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README.md
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---
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base_model: HooshvareLab/bert-base-parsbert-uncased
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- accuracy
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model-index:
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- name: Persian-Text-Sentiment-Bert-LORA
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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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# Persian-Text-Sentiment-Bert-LORA
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This model is a fine-tuned version of [HooshvareLab/bert-base-parsbert-uncased](https://huggingface.co/HooshvareLab/bert-base-parsbert-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3427
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- Precision: 0.8579
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- Recall: 0.8543
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- F1-score: 0.8540
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- Accuracy: 0.8543
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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: 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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:--------:|:--------:|
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| 0.3939 | 1.0 | 3491 | 0.3835 | 0.8457 | 0.8404 | 0.8398 | 0.8404 |
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| 0.3722 | 2.0 | 6982 | 0.3677 | 0.8513 | 0.8457 | 0.8451 | 0.8457 |
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| 0.3553 | 3.0 | 10473 | 0.3576 | 0.8539 | 0.8495 | 0.8491 | 0.8495 |
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| 0.3618 | 4.0 | 13964 | 0.3525 | 0.8546 | 0.8513 | 0.8509 | 0.8513 |
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| 0.3534 | 5.0 | 17455 | 0.3485 | 0.8557 | 0.8521 | 0.8517 | 0.8521 |
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| 0.3423 | 6.0 | 20946 | 0.3470 | 0.8562 | 0.8530 | 0.8526 | 0.8530 |
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| 0.3455 | 7.0 | 24437 | 0.3453 | 0.8573 | 0.8535 | 0.8531 | 0.8535 |
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| 0.347 | 8.0 | 27928 | 0.3428 | 0.8575 | 0.8539 | 0.8535 | 0.8539 |
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| 0.344 | 9.0 | 31419 | 0.3429 | 0.8578 | 0.8546 | 0.8542 | 0.8546 |
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| 0.335 | 10.0 | 34910 | 0.3427 | 0.8579 | 0.8543 | 0.8540 | 0.8543 |
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### Framework versions
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- Transformers 4.35.1
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "HooshvareLab/bert-base-parsbert-uncased",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"lora_alpha": 1,
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"lora_dropout": 0.1,
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 4,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"query",
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"value"
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],
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"task_type": "SEQ_CLS"
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}
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adapter_model.safetensors
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runs/Nov14_19-10-10_731b4cac1cc4/events.out.tfevents.1699989030.731b4cac1cc4.223.0
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runs/Nov14_19-10-10_731b4cac1cc4/events.out.tfevents.1699994579.731b4cac1cc4.223.1
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training_args.bin
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