transformers safetensors distilbert fill-mask generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-finetuned-mol-mlm-0.3
  results: []
---

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# distilbert-base-uncased-finetuned-mol-mlm-0.3

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7283

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.4456        | 1.0   | 210  | 1.0985          |
| 1.055         | 2.0   | 420  | 0.9764          |
| 0.948         | 3.0   | 630  | 0.8907          |
| 0.8698        | 4.0   | 840  | 0.8532          |
| 0.825         | 5.0   | 1050 | 0.8164          |
| 0.7932        | 6.0   | 1260 | 0.7907          |
| 0.7649        | 7.0   | 1470 | 0.7778          |
| 0.7469        | 8.0   | 1680 | 0.7697          |
| 0.7263        | 9.0   | 1890 | 0.7601          |
| 0.7178        | 10.0  | 2100 | 0.7385          |
| 0.7123        | 11.0  | 2310 | 0.7382          |
| 0.7074        | 12.0  | 2520 | 0.7411          |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.15.0
