| train=3000 eval=30 |
|
|
|
processor_config.json: 0%| | 0.00/1.02k [00:00<?, ?B/s][A
processor_config.json: 100%|██████████| 1.02k/1.02k [00:00<00:00, 743kB/s] |
|
|
|
chat_template.jinja: 0%| | 0.00/720 [00:00<?, ?B/s][A
chat_template.jinja: 100%|██████████| 720/720 [00:00<00:00, 4.24MB/s] |
|
|
|
config.json: 0%| | 0.00/2.36k [00:00<?, ?B/s][A
config.json: 100%|██████████| 2.36k/2.36k [00:00<00:00, 15.0MB/s] |
|
|
|
tokenizer_config.json: 0%| | 0.00/5.56k [00:00<?, ?B/s][A
tokenizer_config.json: 100%|██████████| 5.56k/5.56k [00:00<00:00, 31.5MB/s] |
|
|
|
tokenizer.json: reconstructing file: 0%| | 0.00B / 11.4MB [A
tokenizer.json: downloading bytes: | 0.00B
tokenizer.json: downloading bytes: | 33.6kB |
|
tokenizer.json: reconstructing file: 0%| | 28.5kB / 11.4MB [A
tokenizer.json: downloading bytes: ██████████| 3.40MB, 323kB/s
tokenizer.json: downloading bytes: ██████████| 3.40MB, 323kB/s |
|
tokenizer.json: reconstructing file: 100%|██████████| 11.4MB / 11.4MB, 1.09MB/s |
|
|
|
added_tokens.json: 0%| | 0.00/707 [00:00<?, ?B/s][A
added_tokens.json: 100%|██████████| 707/707 [00:00<00:00, 5.24MB/s] |
|
|
|
special_tokens_map.json: 0%| | 0.00/613 [00:00<?, ?B/s][A
special_tokens_map.json: 100%|██████████| 613/613 [00:00<00:00, 3.49MB/s] |
| [transformers] You are using a model of type `mistral3` to instantiate a model of type `lighton_ocr`. This may be expected if you are loading a checkpoint that shares a subset of the architecture (e.g., loading a `sam2_video` checkpoint into `Sam2Model`), but is otherwise not supported and can yield errors. Please verify that the checkpoint is compatible with the model you are instantiating. |
| |
|
model.safetensors: reconstructing file: 0%| | 0.00B / 2.01GB [A
model.safetensors: downloading bytes: | 0.00B |
|
model.safetensors: reconstructing file: 0%| | 39.4kB / 2.01GB [A
model.safetensors: downloading bytes: | 103kB
model.safetensors: downloading bytes: ▏ | 34.7MB, 2.41MB/s
model.safetensors: downloading bytes: ▋ | 147MB, 12.4MB/s |
|
model.safetensors: reconstructing file: 7%|▋ | 134MB / 2.01GB, 19.1kB/s [A
model.safetensors: downloading bytes: █ | 209MB, 17.3MB/s |
|
model.safetensors: reconstructing file: 12%|█▏ | 243MB / 2.01GB, 19.4MB/s [A
model.safetensors: downloading bytes: █▍ | 288MB, 19.9MB/s |
|
model.safetensors: reconstructing file: 18%|█▊ | 354MB / 2.01GB, 24.1MB/s [A
model.safetensors: downloading bytes: ███▌ | 722MB, 51.3MB/s |
|
model.safetensors: reconstructing file: 48%|████▊ | 957MB / 2.01GB, 30.1MB/s [A
model.safetensors: downloading bytes: █████▉ | 1.19GB, 84.6MB/s
model.safetensors: downloading bytes: ████████▎ | 1.68GB, 120MB/s |
|
model.safetensors: reconstructing file: 68%|██████▊ | 1.36GB / 2.01GB, 78.8MB/s [A
model.safetensors: downloading bytes: ██████████| 1.75GB, 122MB/s
model.safetensors: downloading bytes: ██████████| 1.75GB, 122MB/s |
|
model.safetensors: reconstructing file: 100%|██████████| 2.01GB / 2.01GB, 150MB/s |
| |
|
Loading weights: 0%| | 0/532 [00:00<?, ?it/s][A
Loading weights: 100%|██████████| 532/532 [00:00<00:00, 15770.96it/s] |
|
|
|
generation_config.json: 0%| | 0.00/219 [00:00<?, ?B/s][A
generation_config.json: 100%|██████████| 219/219 [00:00<00:00, 1.62MB/s] |
| [eval base] 1/30 cer=0.1851 |
| [eval base] 2/30 cer=0.2617 |
| [eval base] 3/30 cer=0.2774 |
| [eval base] 4/30 cer=0.2012 |
| [eval base] 5/30 cer=0.2754 |
| [eval base] 6/30 cer=0.4906 |
| [eval base] 7/30 cer=0.5578 |
| [eval base] 8/30 cer=0.4953 |
| [eval base] 9/30 cer=0.6164 |
| [eval base] 10/30 cer=0.6604 |
| [eval base] 11/30 cer=0.6920 |
| [eval base] 12/30 cer=0.6875 |
| [eval base] 13/30 cer=0.5397 |
| [eval base] 14/30 cer=0.5463 |
| [eval base] 15/30 cer=0.6926 |
| [eval base] 16/30 cer=0.3421 |
| [eval base] 17/30 cer=0.4329 |
| [eval base] 18/30 cer=0.4298 |
| [eval base] 19/30 cer=0.3960 |
| [eval base] 20/30 cer=0.3732 |
| [eval base] 21/30 cer=0.7938 |
| [eval base] 22/30 cer=0.7542 |
| [eval base] 23/30 cer=0.7598 |
| [eval base] 24/30 cer=0.8000 |
| [eval base] 25/30 cer=1.0146 |
| [eval base] 26/30 cer=1.1248 |
| [eval base] 27/30 cer=1.1429 |
| [eval base] 28/30 cer=1.1569 |
| [eval base] 29/30 cer=1.1456 |
| [eval base] 30/30 cer=1.4049 |
| BASE CER mean=0.6417 median=0.6164 |
| epoch=0 step=5/375 loss=0.1145 lr=4.54e-06 |
| epoch=0 step=10/375 loss=0.0793 lr=9.07e-06 |
| epoch=0 step=15/375 loss=0.0548 lr=9.96e-06 |
| epoch=0 step=20/375 loss=0.0353 lr=9.93e-06 |
| epoch=0 step=25/375 loss=0.0220 lr=9.89e-06 |
| epoch=0 step=30/375 loss=0.0150 lr=9.84e-06 |
| epoch=0 step=35/375 loss=0.0105 lr=9.79e-06 |
| epoch=0 step=40/375 loss=0.0083 lr=9.72e-06 |
| epoch=0 step=45/375 loss=0.0066 lr=9.65e-06 |
| epoch=0 step=50/375 loss=0.0049 lr=9.57e-06 |
| epoch=0 step=55/375 loss=0.0038 lr=9.48e-06 |
| epoch=0 step=60/375 loss=0.0038 lr=9.38e-06 |
| epoch=0 step=65/375 loss=0.0040 lr=9.28e-06 |
| epoch=0 step=70/375 loss=0.0035 lr=9.16e-06 |
| epoch=0 step=75/375 loss=0.0035 lr=9.05e-06 |
| epoch=0 step=80/375 loss=0.0025 lr=8.92e-06 |
| epoch=0 step=85/375 loss=0.0028 lr=8.78e-06 |
| epoch=0 step=90/375 loss=0.0030 lr=8.64e-06 |
| epoch=0 step=95/375 loss=0.0025 lr=8.50e-06 |
| epoch=0 step=100/375 loss=0.0024 lr=8.35e-06 |
| epoch=0 step=105/375 loss=0.0022 lr=8.19e-06 |
| epoch=0 step=110/375 loss=0.0025 lr=8.02e-06 |
| epoch=0 step=115/375 loss=0.0021 lr=7.85e-06 |
| epoch=0 step=120/375 loss=0.0018 lr=7.68e-06 |
| epoch=0 step=125/375 loss=0.0021 lr=7.50e-06 |
| epoch=0 step=130/375 loss=0.0019 lr=7.32e-06 |
| epoch=0 step=135/375 loss=0.0018 lr=7.13e-06 |
| epoch=0 step=140/375 loss=0.0017 lr=6.94e-06 |
| epoch=0 step=145/375 loss=0.0019 lr=6.74e-06 |
| epoch=0 step=150/375 loss=0.0016 lr=6.55e-06 |
| epoch=0 step=155/375 loss=0.0017 lr=6.34e-06 |
| epoch=0 step=160/375 loss=0.0014 lr=6.14e-06 |
| epoch=0 step=165/375 loss=0.0018 lr=5.94e-06 |
| epoch=0 step=170/375 loss=0.0017 lr=5.73e-06 |
| epoch=0 step=175/375 loss=0.0016 lr=5.52e-06 |
| epoch=0 step=180/375 loss=0.0014 lr=5.31e-06 |
| epoch=0 step=185/375 loss=0.0014 lr=5.10e-06 |
| epoch=1 step=190/375 loss=0.0014 lr=4.90e-06 |
| epoch=1 step=195/375 loss=0.0014 lr=4.69e-06 |
| epoch=1 step=200/375 loss=0.0015 lr=4.48e-06 |
| epoch=1 step=205/375 loss=0.0016 lr=4.27e-06 |
| epoch=1 step=210/375 loss=0.0015 lr=4.06e-06 |
| epoch=1 step=215/375 loss=0.0011 lr=3.86e-06 |
| epoch=1 step=220/375 loss=0.0013 lr=3.66e-06 |
| epoch=1 step=225/375 loss=0.0013 lr=3.45e-06 |
| epoch=1 step=230/375 loss=0.0015 lr=3.26e-06 |
| epoch=1 step=235/375 loss=0.0013 lr=3.06e-06 |
| epoch=1 step=240/375 loss=0.0016 lr=2.87e-06 |
| epoch=1 step=245/375 loss=0.0013 lr=2.68e-06 |
| epoch=1 step=250/375 loss=0.0017 lr=2.50e-06 |
| epoch=1 step=255/375 loss=0.0012 lr=2.32e-06 |
| epoch=1 step=260/375 loss=0.0012 lr=2.15e-06 |
| epoch=1 step=265/375 loss=0.0013 lr=1.98e-06 |
| epoch=1 step=270/375 loss=0.0014 lr=1.81e-06 |
| epoch=1 step=275/375 loss=0.0016 lr=1.65e-06 |
| epoch=1 step=280/375 loss=0.0013 lr=1.50e-06 |
| epoch=1 step=285/375 loss=0.0014 lr=1.36e-06 |
| epoch=1 step=290/375 loss=0.0012 lr=1.22e-06 |
| epoch=1 step=295/375 loss=0.0012 lr=1.08e-06 |
| epoch=1 step=300/375 loss=0.0015 lr=1.00e-06 |
| epoch=1 step=305/375 loss=0.0012 lr=1.00e-06 |
| epoch=1 step=310/375 loss=0.0015 lr=1.00e-06 |
| epoch=1 step=315/375 loss=0.0013 lr=1.00e-06 |
| epoch=1 step=320/375 loss=0.0014 lr=1.00e-06 |
| epoch=1 step=325/375 loss=0.0013 lr=1.00e-06 |
| epoch=1 step=330/375 loss=0.0014 lr=1.00e-06 |
| epoch=1 step=335/375 loss=0.0015 lr=1.00e-06 |
| epoch=1 step=340/375 loss=0.0012 lr=1.00e-06 |
| epoch=1 step=345/375 loss=0.0014 lr=1.00e-06 |
| epoch=1 step=350/375 loss=0.0012 lr=1.00e-06 |
| epoch=1 step=355/375 loss=0.0012 lr=1.00e-06 |
| epoch=1 step=360/375 loss=0.0011 lr=1.00e-06 |
| epoch=1 step=365/375 loss=0.0011 lr=1.00e-06 |
| epoch=1 step=370/375 loss=0.0012 lr=1.00e-06 |
| epoch=1 step=375/375 loss=0.0014 lr=1.00e-06 |
| [eval finetuned] 1/30 cer=0.0007 |
| [eval finetuned] 2/30 cer=0.0007 |
| [eval finetuned] 3/30 cer=0.0007 |
| [eval finetuned] 4/30 cer=0.0008 |
| [eval finetuned] 5/30 cer=0.0007 |
| [eval finetuned] 6/30 cer=0.0010 |
| [eval finetuned] 7/30 cer=0.0010 |
| [eval finetuned] 8/30 cer=0.0010 |
| [eval finetuned] 9/30 cer=0.0011 |
| [eval finetuned] 10/30 cer=0.0010 |
| [eval finetuned] 11/30 cer=0.0008 |
| [eval finetuned] 12/30 cer=0.0008 |
| [eval finetuned] 13/30 cer=0.0009 |
| [eval finetuned] 14/30 cer=0.0009 |
| [eval finetuned] 15/30 cer=0.0008 |
| [eval finetuned] 16/30 cer=0.0009 |
| [eval finetuned] 17/30 cer=0.0008 |
| [eval finetuned] 18/30 cer=0.0008 |
| [eval finetuned] 19/30 cer=0.0009 |
| [eval finetuned] 20/30 cer=0.0010 |
| [eval finetuned] 21/30 cer=0.0019 |
| [eval finetuned] 22/30 cer=0.0018 |
| [eval finetuned] 23/30 cer=0.0019 |
| [eval finetuned] 24/30 cer=0.0020 |
| [eval finetuned] 25/30 cer=0.0018 |
| [eval finetuned] 26/30 cer=0.0015 |
| [eval finetuned] 27/30 cer=0.0016 |
| [eval finetuned] 28/30 cer=0.0016 |
| [eval finetuned] 29/30 cer=0.0016 |
| [eval finetuned] 30/30 cer=0.0013 |
| FINETUNED CER mean=0.0012 median=0.0010 |
| |
|
Writing model shards: 0%| | 0/1 [00:00<?, ?it/s][A |
|
Writing model shards: 100%|██████████| 1/1 [00:02<00:00, 2.02s/it][A
Writing model shards: 100%|██████████| 1/1 [00:02<00:00, 2.02s/it] |
| SAVED /w/model |
|
|