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distilrobertta-fin

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railwayBangkok-sentiment-analysis-distilrobertta

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  1. README.md +102 -0
  2. config.json +39 -0
  3. events.out.tfevents.1722221576.cf7f239e2f05.1116.0 +3 -0
  4. events.out.tfevents.1722221779.cf7f239e2f05.1116.1 +3 -0
  5. events.out.tfevents.1722224051.cf7f239e2f05.1116.2 +3 -0
  6. model.safetensors +3 -0
  7. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis
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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: distilrobertta-fin
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+ results: []
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+ ---
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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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+
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+ # distilrobertta-fin
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+
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+ This model is a fine-tuned version of [mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis](https://huggingface.co/mrm8488/distilroberta-finetuned-financial-news-sentiment-analysis) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4084
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+ - Accuracy: 0.8430
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+ - F1: 0.8422
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+ - Precision: 0.8417
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+ - Recall: 0.8434
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 32
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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: 100
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 1.0478 | 0.0820 | 50 | 0.9092 | 0.5421 | 0.4316 | 0.6926 | 0.5431 |
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+ | 0.8397 | 0.1639 | 100 | 0.6847 | 0.6730 | 0.6038 | 0.7467 | 0.6749 |
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+ | 0.6574 | 0.2459 | 150 | 0.5762 | 0.7877 | 0.7764 | 0.7930 | 0.7885 |
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+ | 0.5869 | 0.3279 | 200 | 0.4971 | 0.8144 | 0.8091 | 0.8140 | 0.8149 |
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+ | 0.5599 | 0.4098 | 250 | 0.5133 | 0.8056 | 0.7990 | 0.8079 | 0.8064 |
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+ | 0.5189 | 0.4918 | 300 | 0.4836 | 0.8167 | 0.8105 | 0.8186 | 0.8174 |
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+ | 0.4824 | 0.5738 | 350 | 0.4722 | 0.8256 | 0.8190 | 0.8292 | 0.8262 |
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+ | 0.4592 | 0.6557 | 400 | 0.5095 | 0.8126 | 0.8018 | 0.8243 | 0.8133 |
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+ | 0.4592 | 0.7377 | 450 | 0.4579 | 0.8334 | 0.8291 | 0.8341 | 0.8339 |
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+ | 0.4443 | 0.8197 | 500 | 0.5057 | 0.8134 | 0.8120 | 0.8211 | 0.8131 |
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+ | 0.4845 | 0.9016 | 550 | 0.4407 | 0.8348 | 0.8320 | 0.8337 | 0.8352 |
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+ | 0.4287 | 0.9836 | 600 | 0.4399 | 0.8349 | 0.8317 | 0.8336 | 0.8354 |
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+ | 0.4342 | 1.0656 | 650 | 0.4310 | 0.8317 | 0.8323 | 0.8327 | 0.8319 |
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+ | 0.4615 | 1.1475 | 700 | 0.4514 | 0.8306 | 0.8297 | 0.8300 | 0.8310 |
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+ | 0.402 | 1.2295 | 750 | 0.4553 | 0.8384 | 0.8351 | 0.8407 | 0.8386 |
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+ | 0.3893 | 1.3115 | 800 | 0.4312 | 0.836 | 0.8352 | 0.8348 | 0.8364 |
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+ | 0.4091 | 1.3934 | 850 | 0.4648 | 0.8261 | 0.8170 | 0.8356 | 0.8268 |
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+ | 0.3781 | 1.4754 | 900 | 0.4436 | 0.8316 | 0.8249 | 0.8364 | 0.8322 |
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+ | 0.3814 | 1.5574 | 950 | 0.4700 | 0.8206 | 0.8235 | 0.8330 | 0.8208 |
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+ | 0.3944 | 1.6393 | 1000 | 0.4139 | 0.8437 | 0.8429 | 0.8437 | 0.8438 |
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+ | 0.3961 | 1.7213 | 1050 | 0.4183 | 0.8454 | 0.8434 | 0.8458 | 0.8456 |
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+ | 0.3962 | 1.8033 | 1100 | 0.4255 | 0.8386 | 0.8372 | 0.8413 | 0.8385 |
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+ | 0.4214 | 1.8852 | 1150 | 0.4022 | 0.8435 | 0.8414 | 0.8423 | 0.8438 |
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+ | 0.4058 | 1.9672 | 1200 | 0.4445 | 0.832 | 0.8296 | 0.8365 | 0.8320 |
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+ | 0.3507 | 2.0492 | 1250 | 0.4159 | 0.8444 | 0.8430 | 0.8438 | 0.8446 |
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+ | 0.3535 | 2.1311 | 1300 | 0.4342 | 0.8405 | 0.8377 | 0.8420 | 0.8407 |
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+ | 0.3467 | 2.2131 | 1350 | 0.4208 | 0.8407 | 0.8418 | 0.8448 | 0.8407 |
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+ | 0.3394 | 2.2951 | 1400 | 0.4053 | 0.8476 | 0.8466 | 0.8469 | 0.8478 |
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+ | 0.3344 | 2.3770 | 1450 | 0.4173 | 0.8393 | 0.8410 | 0.8445 | 0.8393 |
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+ | 0.3499 | 2.4590 | 1500 | 0.4050 | 0.848 | 0.8472 | 0.8468 | 0.8483 |
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+ | 0.3245 | 2.5410 | 1550 | 0.4056 | 0.8474 | 0.8465 | 0.8470 | 0.8475 |
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+ | 0.3524 | 2.6230 | 1600 | 0.4002 | 0.8486 | 0.8475 | 0.8473 | 0.8489 |
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+ | 0.3285 | 2.7049 | 1650 | 0.4138 | 0.8446 | 0.8458 | 0.8478 | 0.8447 |
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+ | 0.3269 | 2.7869 | 1700 | 0.4017 | 0.8483 | 0.8478 | 0.8479 | 0.8485 |
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+ | 0.3318 | 2.8689 | 1750 | 0.4012 | 0.8494 | 0.8483 | 0.8481 | 0.8497 |
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+ | 0.3253 | 2.9508 | 1800 | 0.4024 | 0.8476 | 0.8475 | 0.8477 | 0.8477 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Tokenizers 0.19.1
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+ {
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ "attention_probs_dropout_prob": 0.1,
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+ "bos_token_id": 0,
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+ "eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_size": 768,
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 6,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.4",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 50265
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+ }
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