sejalv/seq2seq_model_printed

1---2base_model: microsoft/trocr-small-printed3tags:4- generated_from_trainer5model-index:6- name: seq2seq_model_printed7  results: []8---9 10<!-- This model card has been generated automatically according to the information the Trainer had access to. You11should probably proofread and complete it, then remove this comment. -->12 13# seq2seq_model_printed14 15This model is a fine-tuned version of [microsoft/trocr-small-printed](https://huggingface.co/microsoft/trocr-small-printed) on an unknown dataset.16It achieves the following results on the evaluation set:17- Loss: 1.557818- Cer: 0.213819 20## Model description21 22More information needed23 24## Intended uses & limitations25 26More information needed27 28## Training and evaluation data29 30More information needed31 32## Training procedure33 34### Training hyperparameters35 36The following hyperparameters were used during training:37- learning_rate: 5e-0538- train_batch_size: 239- eval_batch_size: 240- seed: 4241- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0842- lr_scheduler_type: linear43- num_epochs: 3544- mixed_precision_training: Native AMP45 46### Training results47 48| Training Loss | Epoch | Step | Validation Loss | Cer    |49|:-------------:|:-----:|:----:|:---------------:|:------:|50| 4.6751        | 1.0   | 244  | 3.5585          | 1.0652 |51| 3.3624        | 2.0   | 488  | 2.7206          | 0.7373 |52| 2.9125        | 3.0   | 732  | 1.9523          | 0.5418 |53| 2.5734        | 4.0   | 976  | 2.0470          | 0.7149 |54| 2.4143        | 5.0   | 1220 | 1.4577          | 0.3585 |55| 2.2459        | 6.0   | 1464 | 1.5741          | 0.4501 |56| 2.1514        | 7.0   | 1708 | 1.2625          | 0.3218 |57| 2.0268        | 8.0   | 1952 | 1.4816          | 0.3625 |58| 1.9513        | 9.0   | 2196 | 1.6085          | 0.3259 |59| 1.7768        | 10.0  | 2440 | 1.4458          | 0.4033 |60| 1.7156        | 11.0  | 2684 | 1.4845          | 0.3055 |61| 1.5976        | 12.0  | 2928 | 1.6491          | 0.3503 |62| 1.4664        | 13.0  | 3172 | 1.3220          | 0.3381 |63| 1.3276        | 14.0  | 3416 | 1.4486          | 0.3503 |64| 1.2354        | 15.0  | 3660 | 1.6394          | 0.3177 |65| 1.1072        | 16.0  | 3904 | 1.5189          | 0.3035 |66| 0.9209        | 17.0  | 4148 | 1.3820          | 0.2485 |67| 0.7356        | 18.0  | 4392 | 1.4799          | 0.2607 |68| 0.6336        | 19.0  | 4636 | 1.5075          | 0.2220 |69| 0.5035        | 20.0  | 4880 | 1.5413          | 0.2179 |70| 0.406         | 21.0  | 5124 | 1.5602          | 0.2464 |71| 0.3294        | 22.0  | 5368 | 1.4495          | 0.2159 |72| 0.2515        | 23.0  | 5612 | 1.5809          | 0.2240 |73| 0.2207        | 24.0  | 5856 | 1.5188          | 0.2281 |74| 0.1689        | 25.0  | 6100 | 1.5153          | 0.2118 |75| 0.1426        | 26.0  | 6344 | 1.5616          | 0.2118 |76| 0.1142        | 27.0  | 6588 | 1.7044          | 0.2179 |77| 0.0785        | 28.0  | 6832 | 1.6267          | 0.2281 |78| 0.0751        | 29.0  | 7076 | 1.6769          | 0.2159 |79| 0.0507        | 30.0  | 7320 | 1.7316          | 0.2342 |80| 0.0388        | 31.0  | 7564 | 1.5750          | 0.2220 |81| 0.0264        | 32.0  | 7808 | 1.7028          | 0.2159 |82| 0.021         | 33.0  | 8052 | 1.6861          | 0.2322 |83| 0.0195        | 34.0  | 8296 | 1.7154          | 0.2077 |84| 0.0167        | 35.0  | 8540 | 1.5578          | 0.2138 |85 86 87### Framework versions88 89- Transformers 4.42.490- Pytorch 2.1.0a0+b5021ba91- Datasets 2.20.092- Tokenizers 0.19.193