File size: 1,198 Bytes
b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 bb1d65a e59e3c7 b65833f e59e3c7 b65833f e59e3c7 b65833f e59e3c7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 |
---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
model-index:
- name: w2v-bert-fine-tuning
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. -->
# w2v-bert-fine-tuning
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.19.1
|