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htlou/mm-interp-AA_text_image_to_text-llava-mistral

sourceHugging Faceotherupdated 2y agoView on Hugging Face
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Model Card

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AAtextimagetotext

This model is a fine-tuned version of llava-hf/llava-v1.6-mistral-7b-hf on the AAtextimagetotext dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.4527
  • —Rewards/chosen: -0.6857
  • —Rewards/rejected: -4.3940
  • —Rewards/accuracies: 0.8165
  • —Rewards/margins: 3.7083
  • —Logps/rejected: -242.1480
  • —Logps/chosen: -207.1762
  • —Logits/rejected: -2.3240
  • —Logits/chosen: -2.3485

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-06
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 8
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 256
  • —totalevalbatch_size: 64
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 10
  • —num_epochs: 3.0

Training results

Training LossEpochStepValidation LossRewards/chosenRewards/rejectedRewards/accuraciesRewards/marginsLogps/rejectedLogps/chosenLogits/rejectedLogits/chosen
0.48890.2899400.46421.1544-0.18870.79441.3431-200.0950-188.7752-1.9876-2.0351
0.39410.5797800.4218-0.2275-2.29190.80442.0644-221.1273-202.5944-1.9449-1.9901
0.37170.86961200.4387-0.2101-2.48850.82862.2784-223.0936-202.4208-2.0902-2.1229
0.14591.15941600.4288-0.4029-3.39280.82862.9899-232.1363-204.3488-2.2733-2.3007
0.14551.44932000.4255-0.5338-3.63310.81653.0992-234.5387-205.6577-2.2466-2.2697
0.13581.73912400.4247-0.2714-3.67150.83273.4001-234.9227-203.0333-2.3605-2.3806
0.09382.02902800.4128-0.3136-3.70070.82663.3870-235.2147-203.4556-2.3725-2.3933
0.05922.31883200.4438-0.5767-4.12350.81653.5467-239.4429-206.0869-2.3109-2.3358
0.06732.60873600.4553-0.6264-4.30050.82063.6740-241.2126-206.5837-2.3254-2.3497
0.07282.89864000.4520-0.6855-4.39420.81853.7087-242.1503-207.1744-2.3247-2.3492

Framework versions

  • —Transformers 4.45.2
  • —Pytorch 2.4.0+cu121
  • —Datasets 2.21.0
  • —Tokenizers 0.20.3