readme: ---
  tags:
  - generated_from_trainer
  model-index:
  - name: HuMu_TrOCR
    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. -->
  
  # HuMu_TrOCR
  
  This model is a fine-tuned version of [microsoft/trocr-large-stage1](https://huggingface.co/microsoft/trocr-large-stage1) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9161
  - Cer: 0.0777
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 25
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Cer    |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|
  | 2.4312        | 0.08  | 200   | 2.5024          | 0.3614 |
  | 2.3581        | 0.16  | 400   | 2.2241          | 0.3272 |
  | 1.9861        | 0.24  | 600   | 1.9941          | 0.2914 |
  | 2.3043        | 0.33  | 800   | 1.8889          | 0.2586 |
  | 1.5363        | 0.41  | 1000  | 1.9363          | 0.2810 |
  | 1.6588        | 0.49  | 1200  | 1.7219          | 0.2290 |
  | 1.5997        | 0.57  | 1400  | 1.7232          | 0.2398 |
  | 1.4683        | 0.65  | 1600  | 1.7170          | 0.2293 |
  | 1.8478        | 0.73  | 1800  | 1.7417          | 0.2532 |
  | 1.2947        | 0.81  | 2000  | 1.4542          | 0.2023 |
  | 1.1276        | 0.9   | 2200  | 1.5194          | 0.2107 |
  | 1.7701        | 0.98  | 2400  | 1.4983          | 0.2068 |
  | 0.937         | 1.06  | 2600  | 1.4259          | 0.1961 |
  | 1.1816        | 1.14  | 2800  | 1.4410          | 0.1997 |
  | 1.0859        | 1.22  | 3000  | 1.3754          | 0.1879 |
  | 1.2273        | 1.3   | 3200  | 1.4648          | 0.1996 |
  | 0.7966        | 1.38  | 3400  | 1.3127          | 0.1712 |
  | 1.2292        | 1.47  | 3600  | 1.3961          | 0.1942 |
  | 1.081         | 1.55  | 3800  | 1.3005          | 0.1710 |
  | 0.9547        | 1.63  | 4000  | 1.3048          | 0.1739 |
  | 0.756         | 1.71  | 4200  | 1.2821          | 0.1740 |
  | 1.0171        | 1.79  | 4400  | 1.3277          | 0.1741 |
  | 0.7052        | 1.87  | 4600  | 1.2391          | 0.1588 |
  | 0.8321        | 1.95  | 4800  | 1.2030          | 0.1549 |
  | 0.8291        | 2.04  | 5000  | 1.3218          | 0.1759 |
  | 0.8449        | 2.12  | 5200  | 1.2295          | 0.1587 |
  | 0.8244        | 2.2   | 5400  | 1.2597          | 0.1557 |
  | 0.7366        | 2.28  | 5600  | 1.2433          | 0.1524 |
  | 0.9328        | 2.36  | 5800  | 1.2841          | 0.1536 |
  | 0.8448        | 2.44  | 6000  | 1.3028          | 0.1587 |
  | 0.7637        | 2.52  | 6200  | 1.2626          | 0.1482 |
  | 0.9081        | 2.6   | 6400  | 1.3225          | 0.1510 |
  | 0.5485        | 2.69  | 6600  | 1.3118          | 0.1412 |
  | 0.796         | 2.77  | 6800  | 1.3720          | 0.1455 |
  | 1.0663        | 2.85  | 7000  | 1.4572          | 0.1528 |
  | 0.6815        | 2.93  | 7200  | 1.3364          | 0.1466 |
  | 0.494         | 3.01  | 7400  | 1.3676          | 0.1429 |
  | 0.485         | 3.09  | 7600  | 1.5275          | 0.1414 |
  | 0.3569        | 3.17  | 7800  | 1.2862          | 0.1330 |
  | 0.4652        | 3.26  | 8000  | 1.3183          | 0.1312 |
  | 0.5016        | 3.34  | 8200  | 1.3840          | 0.1411 |
  | 0.4985        | 3.42  | 8400  | 1.2660          | 0.1359 |
  | 0.7101        | 3.5   | 8600  | 1.3009          | 0.1423 |
  | 0.5691        | 3.58  | 8800  | 1.3827          | 0.1427 |
  | 0.5115        | 3.66  | 9000  | 1.5285          | 0.1284 |
  | 0.3977        | 3.74  | 9200  | 1.4302          | 0.1369 |
  | 0.6131        | 3.83  | 9400  | 1.5251          | 0.1385 |
  | 0.4959        | 3.91  | 9600  | 1.5062          | 0.1366 |
  | 0.6366        | 3.99  | 9800  | 1.2810          | 0.1334 |
  | 0.3823        | 4.07  | 10000 | 1.5951          | 0.1298 |
  | 0.3339        | 4.15  | 10200 | 1.2864          | 0.1219 |
  | 0.2055        | 4.23  | 10400 | 1.5355          | 0.1279 |
  | 0.4218        | 4.31  | 10600 | 1.5179          | 0.1258 |
  | 0.3051        | 4.4   | 10800 | 1.4567          | 0.1299 |
  | 0.3482        | 4.48  | 11000 | 1.3645          | 0.1277 |
  | 0.4048        | 4.56  | 11200 | 1.5929          | 0.1362 |
  | 0.5023        | 4.64  | 11400 | 1.2703          | 0.1261 |
  | 0.3875        | 4.72  | 11600 | 1.6540          | 0.1286 |
  | 0.4134        | 4.8   | 11800 | 1.2692          | 0.1235 |
  | 0.3848        | 4.88  | 12000 | 1.4234          | 0.1236 |
  | 0.2626        | 4.97  | 12200 | 1.4822          | 0.1218 |
  | 0.2282        | 5.05  | 12400 | 1.3434          | 0.1217 |
  | 0.2806        | 5.13  | 12600 | 1.3007          | 0.1215 |
  