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xlmr-lstm-crf-resume-ner – AI Model by hiendang7613 | AlphaNeural AI
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xlmr-lstm-crf-resume-ner
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transformers
tensorboard
safetensors
xlm-roberta
token-classification
generated_from_trainer
fjd_dataset
FacebookAI/xlm-roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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xlmr-lstm-crf-resume-ner
This model is a fine-tuned version of
xlm-roberta-base
on the fjd_dataset dataset. It achieves the following results on the evaluation set:
eval_loss: 0.1998
eval_precision: 0.5659
eval_recall: 0.6020
eval_f1: 0.5834
eval_accuracy: 0.9475
eval_runtime: 51.9811
eval_samples_per_second: 95.689
eval_steps_per_second: 1.501
epoch: 40.0
step: 18400
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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 100
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1
