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xlm-roberta-en-ru-emoji-v2

Text Classification Transformers PyTorch Safetensors xlm-roberta generated_from_trainer Inference Endpoints
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metadata
tags:
  - generated_from_trainer
metrics:
  - accuracy
base_model: DeepPavlov/xlm-roberta-large-en-ru
model-index:
  - name: xlm-roberta-en-ru-emoji-v2
    results: []

xlm-roberta-en-ru-emoji-v2

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

  • Loss: 2.3356
  • Accuracy: 0.3102

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: 96
  • eval_batch_size: 96
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.4 200 3.0592 0.1204
No log 0.81 400 2.5356 0.2480
2.6294 1.21 600 2.4570 0.2569
2.6294 1.62 800 2.3332 0.2832
1.9286 2.02 1000 2.3354 0.2803
1.9286 2.42 1200 2.3610 0.2881
1.9286 2.83 1400 2.3004 0.2973
1.7312 3.23 1600 2.3619 0.3026
1.7312 3.64 1800 2.3596 0.3032
1.5816 4.04 2000 2.2972 0.3072
1.5816 4.44 2200 2.3077 0.3073
1.5816 4.85 2400 2.3356 0.3102

Framework versions

  • Transformers 4.12.3
  • Pytorch 1.9.1
  • Datasets 1.15.1
  • Tokenizers 0.10.3