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roberta-medium-amharic-32k-256 – AI Model by yosefw | AlphaNeural AI
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roberta-medium-amharic-32k-256
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transformers
tensorboard
safetensors
xlm-roberta
fill-mask
generated_from_trainer
FacebookAI/xlm-roberta-base
finetune
mit
autotrain_compatible
endpoints_compatible
us
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roberta-medium-amharic-32k-256
This model is a fine-tuned version of
FacebookAI/xlm-roberta-base
on an unknown dataset. It achieves the following results on the evaluation set:
eval_loss: 2.4919
eval_model_preparation_time: 0.0026
eval_runtime: 7.3503
eval_samples_per_second: 2968.467
eval_steps_per_second: 11.7
epoch: 31.1537
step: 273405
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: 0.0001
train_batch_size: 256
eval_batch_size: 256
seed: 42
optimizer: Use 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_ratio: 0.1
lr_scheduler_warmup_steps: 10000
num_epochs: 32
mixed_precision_training: Native AMP
Framework versions
Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0
