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dense_ell_100m_multi

This model is a fine-tuned version of on the arrow dataset. It achieves the following results on the evaluation set:

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The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 8
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10534
training_steps: 105347
mixed_precision_training: Native AMP

Training Loss	Epoch	Step	Validation Loss
4.8596	0.9492	10000	4.8075
4.2053	1.8985	20000	4.2042
3.9255	2.8477	30000	4.0088
3.7084	3.7969	40000	3.9207
3.5038	4.7461	50000	3.8968
3.2648	5.6953	60000	3.9192
3.0639	6.6445	70000	3.9761
2.8281	7.5937	80000	4.0612
2.6043	8.5430	90000	4.1459
2.4167	9.4922	100000	4.2128

Safetensors

Model size

0.2B params

Tensor type

F32