Transaminitis_M2_1000rate_1e7_SFT

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.2 on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.2870

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: 1e-07
• train_batch_size: 2
• eval_batch_size: 1
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 100
• training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss
2.2942	0.2	25	2.2327
2.0387	0.4	50	1.9312
1.6442	0.6	75	1.3586
0.7444	0.8	100	0.5869
0.4516	1.0	125	0.4222
0.4019	1.2	150	0.4021
0.3886	1.4	175	0.3923
0.3781	1.6	200	0.3711
0.3635	1.8	225	0.3654
0.3486	2.0	250	0.3536
0.3422	2.2	275	0.3393
0.3271	2.4	300	0.3278
0.3188	2.6	325	0.3180
0.3046	2.8	350	0.3057
0.2926	3.0	375	0.2969
0.2875	3.2	400	0.2926
0.2827	3.4	425	0.2919
0.2894	3.6	450	0.2908
0.2885	3.8	475	0.2890
0.2809	4.0	500	0.2896
0.2764	4.2	525	0.2891
0.2866	4.4	550	0.2884
0.2811	4.6	575	0.2880
0.285	4.8	600	0.2874
0.2791	5.0	625	0.2870
0.2793	5.2	650	0.2872
0.2762	5.4	675	0.2872
0.2783	5.6	700	0.2875
0.2821	5.8	725	0.2869
0.2812	6.0	750	0.2869
0.2795	6.2	775	0.2868
0.2823	6.4	800	0.2868
0.2788	6.6	825	0.2868
0.2764	6.8	850	0.2870
0.2817	7.0	875	0.2869
0.2788	7.2	900	0.2870
0.28	7.4	925	0.2870
0.2862	7.6	950	0.2870
0.2775	7.8	975	0.2870
0.2799	8.0	1000	0.2870

Framework versions

• Transformers 4.40.2
• Pytorch 2.0.0+cu117
• Datasets 2.19.1
• Tokenizers 0.19.1