# Vocabulary Trimmed [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base): `vocabtrimmer/xlm-v-base-trimmed-en` 
This model is a trimmed version of [facebook/xlm-v-base](https://huggingface.co/facebook/xlm-v-base) by [`vocabtrimmer`](https://github.com/asahi417/lm-vocab-trimmer), a tool for trimming vocabulary of language models to compress the model size.
Following table shows a summary of the trimming process.

|                            | facebook/xlm-v-base   | vocabtrimmer/xlm-v-base-trimmed-en   |
|:---------------------------|:----------------------|:-------------------------------------|
| parameter_size_full        | 779,396,349           | 458,814,091                          |
| parameter_size_embedding   | 692,451,072           | 372,285,696                          |
| vocab_size                 | 901,629               | 484,747                              |
| compression_rate_full      | 100.0                 | 58.87                                |
| compression_rate_embedding | 100.0                 | 53.76                                |


Following table shows the parameter used to trim vocabulary.

 | language   | dataset                     | dataset_column   | dataset_name   | dataset_split   | target_vocab_size   |   min_frequency |
|:-----------|:----------------------------|:-----------------|:---------------|:----------------|:--------------------|----------------:|
| en         | vocabtrimmer/mc4_validation | text             | en             | validation      |                     |               2 |
{}
transformers pytorch xlm-roberta fill-mask autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #xlm-roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 

Vocabulary Trimmed facebook/xlm-v-base: 'vocabtrimmer/xlm-v-base-trimmed-en'
============================================================================


This model is a trimmed version of facebook/xlm-v-base by 'vocabtrimmer', a tool for trimming vocabulary of language models to compress the model size.
Following table shows a summary of the trimming process.



Following table shows the parameter used to trim vocabulary.




TAGS
#transformers #pytorch #xlm-roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 

TAGS
#transformers #pytorch #xlm-roberta #fill-mask #autotrain_compatible #endpoints_compatible #region-us 
