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deb101/
mistral-7b-instruct-v0.3-mimic4-adapt-l2r-multilabel-plantclassify

Name: mistral-7b-instruct-v0.3-mimic4-adapt-l2r-multilabel-plantclassify
Availability: InStock

transformers

safetensors

ltr_model

generated_from_trainer

mistralai/Mistral-7B-Instruct-v0.3

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mistral-7b-instruct-v0.3-mimic4-adapt-l2r-multilabel-plantclassify

This model is a fine-tuned version of mistralai/Mistral-7B-Instruct-v0.3 on the None dataset. It achieves the following results on the evaluation set:

F1 Micro: 0.0173
F1 Macro: 0.0083
Precision At 5: 0.4191
Recall At 5: 0.0999
Precision At 8: 0.3571
Recall At 8: 0.1335
Precision At 15: 0.2744
Recall At 15: 0.1864
Rare F1 Micro: 0.0097
Rare F1 Macro: 0.0063
Rare Precision: 0.0049
Rare Recall: 0.6434
Rare Precision At 5: 0.1862
Rare Recall At 5: 0.0670
Rare Precision At 8: 0.1513
Rare Recall At 8: 0.0868
Rare Precision At 15: 0.1107
Rare Recall At 15: 0.1172
Not Rare F1 Micro: 0.1361
Not Rare F1 Macro: 0.1312
Not Rare Precision: 0.0730
Not Rare Recall: 0.9997
Not Rare Precision At 5: 0.4268
Not Rare Recall At 5: 0.2761
Not Rare Precision At 8: 0.3573
Not Rare Recall At 8: 0.3544
Not Rare Precision At 15: 0.2682
Not Rare Recall At 15: 0.4784
Loss: -2.5098

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Use 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: 50
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	F1 Micro	F1 Macro	Precision At 5	Recall At 5	Precision At 8	Recall At 8	Precision At 15	Recall At 15	Rare F1 Micro	Rare F1 Macro	Rare Precision	Rare Recall	Rare Precision At 5	Rare Recall At 5	Rare Precision At 8	Rare Recall At 8	Rare Precision At 15	Rare Recall At 15	Not Rare F1 Micro	Not Rare F1 Macro	Not Rare Precision	Not Rare Recall	Not Rare Precision At 5	Not Rare Recall At 5	Not Rare Precision At 8	Not Rare Recall At 8	Not Rare Precision At 15	Not Rare Recall At 15	Validation Loss
-2.7793	0.9981	262	0.0114	0.0060	0.3790	0.0897	0.3251	0.1194	0.2546	0.1696	0.0065	0.0040	0.0033	0.7152	0.1317	0.0472	0.1068	0.0602	0.0780	0.0804	0.1354	0.1308	0.0726	1.0	0.3727	0.2367	0.3162	0.3110	0.2446	0.4322	-2.3806
-3.0203	1.9981	524	0.0143	0.0070	0.4135	0.0996	0.3589	0.1343	0.2777	0.1888	0.0082	0.0050	0.0041	0.6913	0.1803	0.0641	0.1481	0.0829	0.1086	0.1116	0.1356	0.1309	0.0728	0.9999	0.3987	0.2581	0.3407	0.3388	0.2602	0.4678	-2.4964
-3.2253	2.9981	786	0.0122	0.0069	0.4385	0.1062	0.3724	0.1403	0.2868	0.1941	0.0071	0.0050	0.0036	0.7429	0.1983	0.0713	0.1572	0.0898	0.1142	0.1200	0.1355	0.1308	0.0727	1.0	0.4206	0.2727	0.3544	0.3536	0.2707	0.4839	-2.5382
-3.5758	3.9981	1048	0.0166	0.0082	0.4336	0.1040	0.3683	0.1379	0.2819	0.1919	0.0094	0.0062	0.0047	0.6661	0.1956	0.0704	0.1583	0.0905	0.1155	0.1224	0.1358	0.1310	0.0728	0.9999	0.4260	0.2760	0.3564	0.3548	0.2686	0.4780	-2.5326
-3.9755	4.9981	1310	0.0173	0.0083	0.4191	0.0999	0.3571	0.1335	0.2744	0.1864	0.0097	0.0063	0.0049	0.6434	0.1862	0.0670	0.1513	0.0868	0.1107	0.1172	0.1361	0.1312	0.0730	0.9997	0.4268	0.2761	0.3573	0.3544	0.2682	0.4784	-2.5098

Framework versions

Transformers 4.49.0
Pytorch 2.6.0
Datasets 3.6.0
Tokenizers 0.21.1

deb101/mistral-7b-instruct-v0.3-mimic4-adapt-l2r-multilabel-plantclassify

mistral-7b-instruct-v0.3-mimic4-adapt-l2r-multilabel-plantclassify

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

deb101/
mistral-7b-instruct-v0.3-mimic4-adapt-l2r-multilabel-plantclassify