t5-efficient-base-usdjpy-forecaster

This model is a fine-tuned version of google/t5-efficient-base on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.8988

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: 4
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss
4.0665	0.8430	200	1.0427
3.4826	1.6828	400	0.9274
3.1112	2.5227	600	0.9012
2.9113	3.3625	800	0.8955
2.8138	4.2023	1000	0.8988

Framework versions

• Transformers 5.2.0
• Pytorch 2.10.0+cu128
• Datasets 4.6.0
• Tokenizers 0.22.2