| language: | |
| - la | |
| license: agpl-3.0 | |
| tags: | |
| - robust-speech-event | |
| - hf-asr-leaderboard | |
| datasets: | |
| - lsb/poetaexmachina-mp3-recitations | |
| metrics: | |
| - wer | |
| base_model: wav2vec2-base-it-voxpopuli | |
| model-index: | |
| - name: wav2vec2-base-it-latin | |
| results: | |
| - task: | |
| type: automatic-speech-recognition | |
| name: Speech Recognition | |
| dataset: | |
| name: Poeta Ex Machina mp3 recitations | |
| type: lsb/poetaexmachina-mp3-recitations | |
| metrics: | |
| - type: wer | |
| value: 0.398 | |
| name: Test WER | |
| --- | |
| # wav2vec2-base-it-latin | |
| This model is a fine-tuned version of [wav2vec2-base-it-voxpopuli](https://huggingface.co/facebook/wav2vec2-base-it-voxpopuli) | |
| The dataset used is the [poetaexmachina-mp3-recitations](https://github.com/lsb/poetaexmachina-mp3-recitations), | |
| all of the 2-series texts (vergil) and every tenth 1-series text (words from Poeta Ex Machina's [database](https://github.com/lsb/poetaexmachina/blob/master/merged-scansions.db) of words with scansions). | |
| It achieves the following [results](https://github.com/lsb/tironiculum/blame/trunk/wav2vec2%20base%20it%20latin.ipynb#L1234) on the evaluation set: | |
| - Loss: 0.1943 | |
| - WER: 0.398 | |