adriansanz / 2404v5

huggingface.co
Total runs: 7
24-hour runs: 0
7-day runs: 1
30-day runs: 2
Model's Last Updated: April 24 2024
text-classification

Introduction of 2404v5

Model Details of 2404v5

2404v5

This model is a fine-tuned version of projecte-aina/roberta-base-ca-v2-cased-te on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6586
  • Accuracy: 0.8403
  • Precision: 0.8407
  • Recall: 0.8403
  • F1: 0.8403
  • Ratio: 0.5168
Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 10
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 20
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.06
  • lr_scheduler_warmup_steps: 4
  • num_epochs: 4
  • label_smoothing_factor: 0.1
Training results
Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1 Ratio
3.0551 0.1626 10 1.7145 0.5 0.5 0.5 0.3733 0.0504
1.0346 0.3252 20 0.8860 0.5336 0.5558 0.5336 0.4822 0.8151
0.8531 0.4878 30 0.8174 0.5672 0.6156 0.5672 0.5166 0.1765
0.8279 0.6504 40 0.7147 0.7563 0.7928 0.7563 0.7485 0.6765
0.744 0.8130 50 0.6403 0.8067 0.8099 0.8067 0.8062 0.5504
0.6594 0.9756 60 0.6299 0.7983 0.8004 0.7983 0.7980 0.5420
0.5973 1.1382 70 0.6320 0.8193 0.8204 0.8193 0.8192 0.5294
0.5934 1.3008 80 0.6306 0.8151 0.8184 0.8151 0.8147 0.4496
0.5529 1.4634 90 0.6442 0.8193 0.8195 0.8193 0.8193 0.5126
0.5618 1.6260 100 0.6186 0.8193 0.8204 0.8193 0.8192 0.5294
0.5632 1.7886 110 0.5845 0.8361 0.8373 0.8361 0.8360 0.5294
0.5886 1.9512 120 0.5752 0.8361 0.8367 0.8361 0.8361 0.5210
0.5596 2.1138 130 0.5760 0.8403 0.8407 0.8403 0.8403 0.5168
0.4964 2.2764 140 0.6181 0.8361 0.8367 0.8361 0.8361 0.4790
0.5014 2.4390 150 0.6422 0.8361 0.8381 0.8361 0.8359 0.5378
0.5251 2.6016 160 0.6033 0.8403 0.8428 0.8403 0.8401 0.5420
0.4723 2.7642 170 0.5839 0.8487 0.8503 0.8487 0.8486 0.5336
0.4864 2.9268 180 0.5837 0.8613 0.8616 0.8613 0.8613 0.5126
0.4512 3.0894 190 0.5973 0.8487 0.8491 0.8487 0.8487 0.5168
0.477 3.2520 200 0.6159 0.8403 0.8404 0.8403 0.8403 0.5084
0.4198 3.4146 210 0.6523 0.8403 0.8407 0.8403 0.8403 0.5168
0.4322 3.5772 220 0.6646 0.8403 0.8407 0.8403 0.8403 0.5168
0.4889 3.7398 230 0.6632 0.8403 0.8407 0.8403 0.8403 0.5168
0.4409 3.9024 240 0.6589 0.8403 0.8407 0.8403 0.8403 0.5168
Framework versions
  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1

Runs of adriansanz 2404v5 on huggingface.co

7
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0
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1
3-day runs
1
7-day runs
2
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2404v5 huggingface.co

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adriansanz 2404v5 online free

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adriansanz 2404v5 online free url in huggingface.co:

https://huggingface.co/adriansanz/2404v5

2404v5 install

2404v5 is an open source model from GitHub that offers a free installation service, and any user can find 2404v5 on GitHub to install. At the same time, huggingface.co provides the effect of 2404v5 install, users can directly use 2404v5 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

2404v5 install url in huggingface.co:

https://huggingface.co/adriansanz/2404v5

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adriansanz
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