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multilabel_patent_classifier

Text Classification
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Safetensors
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xlm-roberta
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metadata
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
  - generated_from_trainer
model-index:
  - name: multiclass-classifier-patents
    results: []

multiclass-classifier-patents

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0067
  • F1 Micro: 0.7001
  • Precision Micro: 0.8337
  • Recall Micro: 0.6034
  • Exact Match F1: 0.5296
  • Exact Match Precision: 0.5296
  • Exact Match Recall: 0.5296
  • Any Match F1: 0.9079
  • Any Match Precision: 0.9079
  • Any Match Recall: 0.9079

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: 2e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 Micro Precision Micro Recall Micro Exact Match F1 Exact Match Precision Exact Match Recall Any Match F1 Any Match Precision Any Match Recall
0.01 1.0 1292 0.0083 0.5977 0.8265 0.4681 0.4300 0.4300 0.4300 0.7675 0.7675 0.7675
0.0077 2.0 2584 0.0074 0.6595 0.8326 0.5460 0.4879 0.4879 0.4879 0.8636 0.8636 0.8636
0.007 3.0 3876 0.0071 0.6829 0.8173 0.5864 0.5035 0.5035 0.5035 0.8958 0.8958 0.8958
0.0063 4.0 5168 0.0069 0.6883 0.8317 0.5871 0.5140 0.5140 0.5140 0.8956 0.8956 0.8956
0.0058 5.0 6460 0.0068 0.6957 0.8337 0.5969 0.5182 0.5182 0.5182 0.9058 0.9058 0.9058
0.0053 6.0 7752 0.0069 0.6999 0.8366 0.6017 0.5271 0.5271 0.5271 0.9082 0.9082 0.9082
0.0048 7.0 9044 0.0069 0.7046 0.8159 0.6201 0.5225 0.5225 0.5225 0.9185 0.9185 0.9185
0.0046 8.0 10336 0.0069 0.7069 0.8100 0.6271 0.5241 0.5241 0.5241 0.9196 0.9196 0.9196
0.0042 9.0 11628 0.0070 0.7064 0.8208 0.6200 0.5282 0.5282 0.5282 0.9174 0.9174 0.9174
0.004 10.0 12920 0.0070 0.7064 0.8184 0.6214 0.5276 0.5276 0.5276 0.9177 0.9177 0.9177

Framework versions

  • Transformers 4.45.2
  • Pytorch 2.0.1+cu117
  • Datasets 3.0.1
  • Tokenizers 0.20.3