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classical-modern-chinese-translator – AI Model by Danielwei0214 | AlphaNeural AI
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classical-modern-chinese-translator
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transformers
safetensors
mt5
text2text-generation
generated_from_trainer
google/mt5-small
finetune
apache-2.0
endpoints_compatible
us
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classical-modern-chinese-translator
This model is a fine-tuned version of
google/mt5-small
on the None dataset. It achieves the following results on the evaluation set:
Loss: nan
Bleu: 0
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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Bleu
0.0
1.0
25747
nan
0
0.0
2.0
51494
nan
0
0.0
2.9999
77238
nan
0
Framework versions
Transformers 4.48.2
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0
