End of training

README.md

@@ -0,0 +1,74 @@
+---
+license: mit
+base_model: naver-clova-ix/donut-base
+tags:
+- generated_from_trainer
+metrics:
+- bleu
+- wer
+model-index:
+- name: donut_experiment_bayesian_trial_6
+  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. -->
+
+# donut_experiment_bayesian_trial_6
+
+This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5515
+- Bleu: 0.0683
+- Precisions: [0.8127572016460906, 0.7412587412587412, 0.6854838709677419, 0.638095238095238]
+- Brevity Penalty: 0.0954
+- Length Ratio: 0.2985
+- Translation Length: 486
+- Reference Length: 1628
+- Cer: 0.7532
+- Wer: 0.8274
+
+## 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: 0.00016063260663724173
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 2
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 4
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Bleu   | Precisions                                                                       | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer    | Wer    |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
+| 0.3276        | 1.0   | 253  | 0.6672          | 0.0589 | [0.76875, 0.6737588652482269, 0.6092896174863388, 0.5436893203883495]            | 0.0915          | 0.2948       | 480                | 1628             | 0.7586 | 0.8473 |
+| 0.2008        | 2.0   | 506  | 0.5780          | 0.0662 | [0.7905544147843943, 0.7069767441860465, 0.6595174262734584, 0.6107594936708861] | 0.0960          | 0.2991       | 487                | 1628             | 0.7559 | 0.8374 |
+| 0.1356        | 3.0   | 759  | 0.5355          | 0.0651 | [0.8238993710691824, 0.7452380952380953, 0.6942148760330579, 0.6535947712418301] | 0.0895          | 0.2930       | 477                | 1628             | 0.7580 | 0.8299 |
+| 0.0394        | 4.0   | 1012 | 0.5515          | 0.0683 | [0.8127572016460906, 0.7412587412587412, 0.6854838709677419, 0.638095238095238]  | 0.0954          | 0.2985       | 486                | 1628             | 0.7532 | 0.8274 |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.1.0
+- Datasets 2.18.0
+- Tokenizers 0.19.1

added_tokens.json

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+{
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+  "</s_company>": 57530,
+  "</s_date>": 57528,
+  "</s_total>": 57526,
+  "<s_address>": 57531,
+  "<s_company>": 57529,
+  "<s_date>": 57527,
+  "<s_iitcdip>": 57523,
+  "<s_synthdog>": 57524,
+  "<s_total>": 57525,
+  "<sep/>": 57522
+}

generation_config.json

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+{
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "forced_eos_token_id": 2,
+  "pad_token_id": 1,
+  "transformers_version": "4.40.0"
+}

metrics.jsonl

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 {"eval_loss": 0.6671950817108154, "eval_bleu": 0.05887466031932394, "eval_precisions": [0.76875, 0.6737588652482269, 0.6092896174863388, 0.5436893203883495], "eval_brevity_penalty": 0.09147709493048638, "eval_length_ratio": 0.29484029484029484, "eval_translation_length": 480, "eval_reference_length": 1628, "eval_cer": 0.7585635206212383, "eval_wer": 0.8473100066521295, "eval_runtime": 73.9699, "eval_samples_per_second": 0.771, "eval_steps_per_second": 0.771, "epoch": 1.0}
 {"eval_loss": 0.5779862403869629, "eval_bleu": 0.06615961071974022, "eval_precisions": [0.7905544147843943, 0.7069767441860465, 0.6595174262734584, 0.6107594936708861], "eval_brevity_penalty": 0.09604717412371518, "eval_length_ratio": 0.29914004914004916, "eval_translation_length": 487, "eval_reference_length": 1628, "eval_cer": 0.755914417349584, "eval_wer": 0.8374108424924571, "eval_runtime": 74.0665, "eval_samples_per_second": 0.77, "eval_steps_per_second": 0.77, "epoch": 2.0}
 {"eval_loss": 0.5355449914932251, "eval_bleu": 0.06505658339188798, "eval_precisions": [0.8238993710691824, 0.7452380952380953, 0.6942148760330579, 0.6535947712418301], "eval_brevity_penalty": 0.08954644018167994, "eval_length_ratio": 0.292997542997543, "eval_translation_length": 477, "eval_reference_length": 1628, "eval_cer": 0.7580146108810044, "eval_wer": 0.8298783893916056, "eval_runtime": 74.1467, "eval_samples_per_second": 0.769, "eval_steps_per_second": 0.769, "epoch": 3.0}
+{"eval_loss": 0.5515202879905701, "eval_bleu": 0.06834404481266766, "eval_precisions": [0.8127572016460906, 0.7412587412587412, 0.6854838709677419, 0.638095238095238], "eval_brevity_penalty": 0.095388787518951, "eval_length_ratio": 0.2985257985257985, "eval_translation_length": 486, "eval_reference_length": 1628, "eval_cer": 0.7531764673711733, "eval_wer": 0.82739464735678, "eval_runtime": 74.1222, "eval_samples_per_second": 0.769, "eval_steps_per_second": 0.769, "epoch": 4.0}

preprocessor_config.json

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+{
+  "_valid_processor_keys": [
+    "images",
+    "do_resize",
+    "size",
+    "resample",
+    "do_thumbnail",
+    "do_align_long_axis",
+    "do_pad",
+    "random_padding",
+    "do_rescale",
+    "rescale_factor",
+    "do_normalize",
+    "image_mean",
+    "image_std",
+    "return_tensors",
+    "data_format",
+    "input_data_format"
+  ],
+  "do_align_long_axis": false,
+  "do_normalize": true,
+  "do_pad": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "do_thumbnail": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
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+  "image_processor_type": "DonutImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
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+  "processor_class": "DonutProcessor",
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": [
+    720,
+    960
+  ]
+}

runs/May30_17-10-13_ip-172-16-168-165.ec2.internal/events.out.tfevents.1717089014.ip-172-16-168-165.ec2.internal.8916.4

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sentencepiece.bpe.model

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special_tokens_map.json

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tokenizer_config.json

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+}