Model save

README.md

@@ -1,11 +1,58 @@
 ---
-license: mit
-language:
-- en
-metrics:
-- character
-library_name: transformers
-pipeline_tag: image-to-text
+base_model: microsoft/trocr-base-handwritten
 tags:
-- code
----
+- generated_from_trainer
+model-index:
+- name: license_plate_recognizer
+  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. -->
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/pawankrgunjan/huggingface/runs/ccr8xsj5)
+# license_plate_recognizer
+
+This model is a fine-tuned version of [microsoft/trocr-base-handwritten](https://huggingface.co/microsoft/trocr-base-handwritten) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0696
+- Cer: 0.0231
+
+## 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: 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: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Cer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|
+| 0.333         | 1.0   | 254  | 0.0554          | 0.0164 |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

generation_config.json

@@ -0,0 +1,11 @@
+{
+  "bos_token_id": 0,
+  "decoder_start_token_id": 0,
+  "early_stopping": true,
+  "eos_token_id": 2,
+  "max_length": 128,
+  "num_beams": 3,
+  "pad_token_id": 1,
+  "transformers_version": "4.42.3",
+  "use_cache": false
+}