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---
license: mit
base_model: microsoft/kosmos-2-patch14-224
tags:
- generated_from_trainer
model-index:
- name: kosm-checkpoint
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. -->
# kosm-checkpoint
This model is a fine-tuned version of [microsoft/kosmos-2-patch14-224](https://huggingface.co/microsoft/kosmos-2-patch14-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0340
## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| No log | 0.0497 | 200 | 0.0700 |
| 0.0802 | 0.0993 | 400 | 0.0581 |
| 0.0676 | 0.1490 | 600 | 0.0496 |
| 0.0584 | 0.1986 | 800 | 0.0450 |
| 0.0582 | 0.2483 | 1000 | 0.0481 |
| 0.0582 | 0.2979 | 1200 | 0.0486 |
| 0.0572 | 0.3476 | 1400 | 0.0445 |
| 0.0537 | 0.3972 | 1600 | 0.0463 |
| 0.0504 | 0.4469 | 1800 | 0.0421 |
| 0.0473 | 0.4965 | 2000 | 0.0402 |
| 0.0473 | 0.5462 | 2200 | 0.0423 |
| 0.046 | 0.5958 | 2400 | 0.0394 |
| 0.0448 | 0.6455 | 2600 | 0.0369 |
| 0.0423 | 0.6951 | 2800 | 0.0378 |
| 0.0403 | 0.7448 | 3000 | 0.0360 |
| 0.0403 | 0.7944 | 3200 | 0.0364 |
| 0.0392 | 0.8441 | 3400 | 0.0352 |
| 0.0388 | 0.8937 | 3600 | 0.0347 |
| 0.0375 | 0.9434 | 3800 | 0.0343 |
| 0.037 | 0.9930 | 4000 | 0.0345 |
| 0.037 | 1.0427 | 4200 | 0.0355 |
| 0.03 | 1.0924 | 4400 | 0.0338 |
| 0.0283 | 1.1420 | 4600 | 0.0349 |
| 0.0281 | 1.1917 | 4800 | 0.0347 |
| 0.0288 | 1.2413 | 5000 | 0.0322 |
| 0.0288 | 1.2910 | 5200 | 0.0331 |
| 0.0279 | 1.3406 | 5400 | 0.0335 |
| 0.0272 | 1.3903 | 5600 | 0.0322 |
| 0.0275 | 1.4399 | 5800 | 0.0338 |
| 0.0271 | 1.4896 | 6000 | 0.0324 |
| 0.0271 | 1.5392 | 6200 | 0.0324 |
| 0.0263 | 1.5889 | 6400 | 0.0320 |
| 0.0262 | 1.6385 | 6600 | 0.0319 |
| 0.0264 | 1.6882 | 6800 | 0.0317 |
| 0.0256 | 1.7378 | 7000 | 0.0322 |
| 0.0256 | 1.7875 | 7200 | 0.0320 |
| 0.0255 | 1.8371 | 7400 | 0.0316 |
| 0.0242 | 1.8868 | 7600 | 0.0327 |
| 0.0262 | 1.9364 | 7800 | 0.0307 |
| 0.0252 | 1.9861 | 8000 | 0.0304 |
| 0.0252 | 2.0357 | 8200 | 0.0343 |
| 0.0173 | 2.0854 | 8400 | 0.0373 |
| 0.0148 | 2.1351 | 8600 | 0.0345 |
| 0.015 | 2.1847 | 8800 | 0.0347 |
| 0.0148 | 2.2344 | 9000 | 0.0347 |
| 0.0148 | 2.2840 | 9200 | 0.0354 |
| 0.0132 | 2.3337 | 9400 | 0.0351 |
| 0.0136 | 2.3833 | 9600 | 0.0362 |
| 0.0132 | 2.4330 | 9800 | 0.0360 |
| 0.0138 | 2.4826 | 10000 | 0.0352 |
| 0.0138 | 2.5323 | 10200 | 0.0359 |
| 0.0138 | 2.5819 | 10400 | 0.0348 |
| 0.0132 | 2.6316 | 10600 | 0.0348 |
| 0.0129 | 2.6812 | 10800 | 0.0337 |
| 0.0134 | 2.7309 | 11000 | 0.0354 |
| 0.0134 | 2.7805 | 11200 | 0.0350 |
| 0.0132 | 2.8302 | 11400 | 0.0351 |
| 0.0128 | 2.8798 | 11600 | 0.0350 |
| 0.013 | 2.9295 | 11800 | 0.0339 |
| 0.012 | 2.9791 | 12000 | 0.0340 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.19.1
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