Mistral_Sparse_refined_web_50p_2024-02-16 – AI Model by thrunlab | AlphaNeural AI

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thrunlab/
Mistral_Sparse_refined_web_50p_2024-02-16

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text-generation

generated_from_trainer

mistralai/Mistral-7B-v0.1

autotrain_compatible

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Mistral_Sparse_refined_web_50p_2024-02-16

This model is a fine-tuned version of mistralai/Mistral-7B-v0.1 on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.1260

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-05
train_batch_size: 1
eval_batch_size: 1
seed: 0
distributed_type: multi-GPU
num_devices: 3
gradient_accumulation_steps: 3
total_train_batch_size: 9
total_eval_batch_size: 3
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 1000

Training results

Training Loss	Epoch	Step	Validation Loss
2.5975	0.01	25	2.6362
2.3082	0.01	50	2.5659
2.4024	0.02	75	2.5151
2.3358	0.02	100	2.4817
2.2267	0.03	125	2.4660
2.271	0.04	150	2.4456
2.1709	0.04	175	2.4413
2.2549	0.05	200	2.4306
2.2536	0.05	225	2.4243
2.2234	0.06	250	2.4212
2.2516	0.07	275	2.4202
2.2827	0.07	300	2.4146
2.1774	0.08	325	2.4156
2.278	0.08	350	2.4094
2.204	0.09	375	2.4088
2.1987	0.1	400	2.4073
2.1985	0.1	425	2.4041
2.2198	0.11	450	2.4069
2.2555	0.11	475	2.4014
2.1567	0.12	500	2.4017
2.2918	0.13	525	2.3998
2.2559	0.13	550	2.3959
2.2234	0.14	575	2.3978
2.2001	0.14	600	2.3944
2.1409	0.15	625	2.3957
2.2034	0.16	650	2.3981
2.1863	0.16	675	2.3941
2.2372	0.17	700	2.3936
2.2438	0.17	725	2.3953
2.2172	0.18	750	2.3943
2.1917	0.19	775	2.3921
2.1137	0.19	800	2.3912
2.0766	0.07	825	2.3935
2.1926	0.08	850	2.3913
2.2948	0.08	875	2.3915
2.1349	0.08	900	2.3917
2.2446	0.08	925	2.3876
2.253	0.09	950	2.3880
2.0729	0.09	975	2.3890
2.1965	0.09	1000	2.3873

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.15.0
Tokenizers 0.15.0