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Exp23 Directfit Unfrozen

This model is a fine-tuned version of cyttic/exp22-exp2warm-directfit-frozen on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.4588 Cer: 0.0245 Wer: 0.0647

Sourcehuggingface.co/cyttic/exp23-directfit-unfrozen/tree/57b28f8ac5e8e2d9ff910b7126efbda032fa2a8d
KindCheckpointBase modelcyttic/exp22-exp2warm-directfit-frozenVersionRevision 57b28f8Dgrade

Model source

Kind
Checkpoint
File size
1.12 GB
Base model
cyttic/exp22-exp2warm-directfit-frozen
Version
vRevision 57b28f8
Updated
Oct 1, 2026
Downloads
173
Source
Hugging Face

Source description

exp23-directfit-unfrozen

This model is a fine-tuned version of cyttic/exp22-exp2warm-directfit-frozen on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4588
  • Cer: 0.0245
  • Wer: 0.0647

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: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
  • num_epochs: 1

Training results

Training LossEpochStepValidation LossCerWer
1.25770.042425001.33780.14160.2986
1.04130.084850001.24410.11500.2561
0.84360.127275001.08540.09170.2106
0.77620.1696100000.93140.07350.1700
0.70960.2120125000.89540.06270.1534
0.62050.2544150000.79070.05500.1378
0.58730.2968175000.74080.04860.1215
0.55040.3392200000.68940.04270.1112
0.48260.3816225000.65370.04060.1042
0.52240.4240250000.62450.03800.0965
0.44300.4664275000.58660.03660.0933
0.42190.5088300000.57240.03400.0873
0.35570.5512325000.55860.03180.0849
0.38660.5936350000.53990.03280.0845
0.35860.6360375000.52670.03050.0793
0.40090.6784400000.50820.03010.0769
0.31400.7208425000.50110.02890.0740
0.34350.7632450000.48740.02760.0725
0.31410.8056475000.48070.02670.0691
0.32000.8480500000.47380.02670.0687
0.32010.8904525000.46820.02500.0664
0.33140.9328550000.46330.02490.0652
0.34270.9752575000.46040.02440.0648
0.30201.0589620.45880.02450.0647

Framework versions

  • Transformers 5.12.1
  • Pytorch 2.11.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Sources

1 source
Hugging FacePrimaryVersion 57b28f8ac5e8e2d9ff910b7126efbda032fa2a8d
huggingface.co/cyttic/exp23-directfit-unfrozen/tree/57b28f8ac5e8e2d9ff910b7126efbda032fa2a8d

Verified Oct 1

Model artifacts

2 artifacts

last-checkpoint/model.safetensors

safetensors · 1.12 GB · SHA-256 f4206fdf41f5…d1c9 · Hugging Face

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model.safetensors

safetensors · 1.12 GB · SHA-256 f4206fdf41f5…d1c9 · Hugging Face

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Source excerpts

3 excerpts
ReadmeJul 11huggingface.co/cyttic/exp23-directfit-unfrozen

--- library_name: transformers base_model: cyttic/exp22-exp2warm-directfit-frozen tags: - generated_from_trainer metrics: - wer model-index: - name: exp23-directfit-unfrozen results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # exp23-directfit-unfrozen This model is a fine-tuned version of [cyttic/exp22-exp2warm-directfit-frozen](https://huggingface.co/cyttic/exp22-exp2warm-directfit-frozen) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.4588 - Cer: 0.0245 - Wer: 0.0647 ## 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: 16 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1 - num_epochs: 1 ### Training results | Training Loss | Epoch | Step | Validation Loss | Cer | Wer | |:-------------:|:------:|:-----:|:---------------:|:------:|:------:| | 1.2577 | 0.0424 | 2500 | 1.3378 | 0.1416 | 0.2986 | | 1.0413 | 0.0848 | 5000 | 1.2441 | 0.1150 | 0.2561 | | 0.8436 | 0.1272 | 7500 | 1.0854 | 0.0917 | 0.2106 | | 0.7762 | 0.1696 | 10000 | 0.9314 | 0.0735 | 0.1700 | | 0.7096 | 0.2120 | 12500 | 0.8954 | 0.0627 | 0.1534 | | 0.6205 | 0.2544 | 15000 | 0.7907 | 0.0550 | 0.1378 | | 0.5873 | 0.2968 | 17500 | 0.7408 | 0.0486 | 0.1215 | | 0.5504 | 0.3392 | 20000 | 0.6894 | 0.0427 | 0.1112 | | 0.4826 | 0.3816 | 22500 | 0.6537 | 0.0406 | 0.1042 | | 0.5224 | 0.4240 | 25000 | 0.6245 | 0.0380 | 0.0965 | | 0.4430 | 0.4664 | 27500 | 0.5866 | 0.0366 | 0.0933 | | 0.4219 | 0.5088 | 30000 | 0.5724 | 0.0340 | 0.0873 | | 0.3557 | 0.5512 | 32500 | 0.5586 | 0.0318 | 0.0849 | | 0.3866 | 0.5936 | 35000 | 0.5399 | 0.0328 | 0.0845 | | 0.3586 | 0.6360 | 37500 | 0.5267 | 0.0305 | 0.0793 | | 0.4009 | 0.6784 | 40000 | 0.5082 | 0.0301 | 0.0769 | | 0.3140 | 0.7208 | 42500 | 0.5011 | 0.0289 | 0.0740 | | 0.3435 | 0.7632 | 45000 | 0.4874 | 0.0276 | 0.0725 | | 0.314...

NoteOct 1huggingface.co/cyttic/exp23-directfit-unfrozen

Source context: 173 downloads · 1 likes · Pipeline image-text-to-text · Library transformers · Repo cyttic/exp23-directfit-unfrozen

NoteJul 16huggingface.co/cyttic/exp23-directfit-unfrozen

Source context: 467 downloads · 1 likes · Pipeline image-text-to-text · Library transformers · Repo cyttic/exp23-directfit-unfrozen