lemexp-processed-task1_min_symbols_lemma_object_small-deepseek-coder-1.3b-base

This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2167

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: 0.0002
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• 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: 100
• num_epochs: 6
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.4548	0.2000	5030	0.4143
0.3861	0.4001	10060	0.3652
0.3504	0.6001	15090	0.3359
0.3352	0.8001	20120	0.3129
0.3186	1.0002	25150	0.3011
0.2763	1.2002	30180	0.2905
0.2711	1.4002	35210	0.2776
0.2579	1.6003	40240	0.2743
0.2484	1.8003	45270	0.2600
0.263	2.0003	50300	0.2602
0.2108	2.2003	55330	0.2580
0.2026	2.4004	60360	0.2526
0.2228	2.6004	65390	0.2473
0.2187	2.8004	70420	0.2387
0.2053	3.0005	75450	0.2345
0.1761	3.2005	80480	0.2379
0.1773	3.4005	85510	0.2323
0.1689	3.6006	90540	0.2265
0.1707	3.8006	95570	0.2256
0.1764	4.0006	100600	0.2197
0.1377	4.2007	105630	0.2262
0.1485	4.4007	110660	0.2230
0.1464	4.6007	115690	0.2161
0.1521	4.8008	120720	0.2178
0.1457	5.0008	125750	0.2144
0.1146	5.2008	130780	0.2221
0.1187	5.4009	135810	0.2204
0.1041	5.6009	140840	0.2201
0.1171	5.8009	145870	0.2167

Framework versions

• PEFT 0.14.0
• Transformers 4.47.0
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0