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README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- sagawa/pubchem-10m-canonicalized
+metrics:
+- accuracy
+model-index:
+- name: PubChem10m-deberta-base-output
+  results:
+  - task:
+      name: Masked Language Modeling
+      type: fill-mask
+    dataset:
+      name: sagawa/pubchem-10m-canonicalized
+      type: sagawa/pubchem-10m-canonicalized
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9741235263046233
+---
+
+<!-- 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. -->
+
+# PubChem10m-deberta-base-output
+
+This model is a fine-tuned version of [microsoft/deberta-base](https://huggingface.co/microsoft/deberta-base) on the sagawa/pubchem-10m-canonicalized dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0698
+- Accuracy: 0.9741
+
+## 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: 30
+- eval_batch_size: 48
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10.0
+
+### Training results
+
+| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
+|:-------------:|:-----:|:------:|:---------------:|:--------:|
+| 0.0855        | 3.68  | 100000 | 0.0801          | 0.9708   |
+| 0.0733        | 7.37  | 200000 | 0.0702          | 0.9740   |
+
+
+### Framework versions
+
+- Transformers 4.22.0.dev0
+- Pytorch 1.12.0
+- Datasets 2.4.1.dev0
+- Tokenizers 0.11.6

config.json

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+  "model_type": "deberta",
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+  "pooler_hidden_size": 768,
+  "pos_att_type": [
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+  "torch_dtype": "float32",
+  "transformers_version": "4.22.0.dev0",
+  "type_vocab_size": 0,
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+}

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