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lora-roberta-large-0927

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README.md ADDED
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+ ---
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+ license: mit
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+ base_model: roberta-large
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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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+ - recall
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+ - f1
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+ model-index:
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+ - name: lora-roberta-large-0927
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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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+ # lora-roberta-large-0927
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+
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+ This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.5356
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+ - Accuracy: 0.4472
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+ - Prec: 0.2000
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+ - Recall: 0.4472
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+ - F1: 0.2763
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+ - B Acc: 0.1429
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+ - Micro F1: 0.4472
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+ - Prec Joy: 0.0
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+ - Recall Joy: 0.0
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+ - F1 Joy: 0.0
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+ - Prec Anger: 0.0
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+ - Recall Anger: 0.0
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+ - F1 Anger: 0.0
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+ - Prec Disgust: 0.0
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+ - Recall Disgust: 0.0
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+ - F1 Disgust: 0.0
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+ - Prec Fear: 0.0
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+ - Recall Fear: 0.0
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+ - F1 Fear: 0.0
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+ - Prec Neutral: 0.4472
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+ - Recall Neutral: 1.0
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+ - F1 Neutral: 0.6180
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+ - Prec Sadness: 0.0
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+ - Recall Sadness: 0.0
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+ - F1 Sadness: 0.0
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+ - Prec Surprise: 0.0
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+ - Recall Surprise: 0.0
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+ - F1 Surprise: 0.0
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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: 0.001
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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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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_ratio: 0.05
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+ - num_epochs: 25.0
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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 | Prec | Recall | F1 | B Acc | Micro F1 | Prec Joy | Recall Joy | F1 Joy | Prec Anger | Recall Anger | F1 Anger | Prec Disgust | Recall Disgust | F1 Disgust | Prec Fear | Recall Fear | F1 Fear | Prec Neutral | Recall Neutral | F1 Neutral | Prec Sadness | Recall Sadness | F1 Sadness | Prec Surprise | Recall Surprise | F1 Surprise |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|:--------:|:--------:|:----------:|:------:|:----------:|:------------:|:--------:|:------------:|:--------------:|:----------:|:---------:|:-----------:|:-------:|:------------:|:--------------:|:----------:|:------------:|:--------------:|:----------:|:-------------:|:---------------:|:-----------:|
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+ | 0.8381 | 1.25 | 2092 | 1.5415 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4866 | 2.5 | 4184 | 1.5564 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4862 | 3.75 | 6276 | 1.5700 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4762 | 5.0 | 8368 | 1.5391 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4765 | 6.25 | 10460 | 1.5566 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4848 | 7.5 | 12552 | 1.5411 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4782 | 8.75 | 14644 | 1.5548 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4943 | 10.0 | 16736 | 1.6115 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4801 | 11.25 | 18828 | 1.5424 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4946 | 12.5 | 20920 | 1.5637 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4867 | 13.75 | 23012 | 1.5492 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4957 | 15.01 | 25104 | 1.5812 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4913 | 16.26 | 27196 | 1.5425 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.5007 | 17.51 | 29288 | 1.5446 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4919 | 18.76 | 31380 | 1.5616 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4895 | 20.01 | 33472 | 1.5502 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4946 | 21.26 | 35564 | 1.5398 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4754 | 22.51 | 37656 | 1.5307 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 1.4824 | 23.76 | 39748 | 1.5356 | 0.4472 | 0.2000 | 0.4472 | 0.2763 | 0.1429 | 0.4472 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.4472 | 1.0 | 0.6180 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.1
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+ - Pytorch 2.0.1
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+ - Datasets 2.12.0
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+ - Tokenizers 0.13.3
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