tinyllama_mole_sft_ultrachat_ep3

This model was trained from scratch on the generator dataset. It achieves the following results on the evaluation set:

• Loss: 1.1127

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 2
• total_train_batch_size: 128
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 120
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.3007	0.09	100	1.2780
1.2255	0.18	200	1.2158
1.192	0.26	300	1.1921
1.1696	0.35	400	1.1770
1.1426	0.44	500	1.1666
1.1628	0.53	600	1.1583
1.1501	0.61	700	1.1513
1.137	0.7	800	1.1457
1.1321	0.79	900	1.1407
1.1156	0.88	1000	1.1359
1.1395	0.96	1100	1.1318
1.0564	1.05	1200	1.1315
1.0594	1.14	1300	1.1295
1.0711	1.23	1400	1.1274
1.0624	1.31	1500	1.1256
1.0652	1.4	1600	1.1233
1.0626	1.49	1700	1.1213
1.0457	1.58	1800	1.1195
1.0665	1.66	1900	1.1178
1.07	1.75	2000	1.1158
1.0567	1.84	2100	1.1141
1.0304	1.93	2200	1.1127
1.0132	2.01	2300	1.1170
1.0203	2.1	2400	1.1170
1.0088	2.19	2500	1.1168
1.002	2.28	2600	1.1162
1.0004	2.37	2700	1.1157
1.0058	2.45	2800	1.1156
1.0118	2.54	2900	1.1150
0.9941	2.63	3000	1.1148
1.0127	2.72	3100	1.1147
1.0039	2.8	3200	1.1144
1.0	2.89	3300	1.1143
1.0188	2.98	3400	1.1143

Framework versions

• Transformers 4.37.0
• Pytorch 2.1.2+cu118
• Datasets 2.16.1
• Tokenizers 0.15.0