add tokenizer

README.md

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+---
+---
+language:
+- la
+license: agpl-3.0
+tags:
+- robust-speech-event
+datasets:
+- lsb/poetaexmachina-mp3-recitations
+metrics:
+- wer
+model-index:
+- name: wav2vec2-base-it-latin
+  results:
+    - task:
+        type: automatic-speech-recognition
+        name: Speech Recognition
+      dataset:
+        type: lsb/poetaexmachina-mp3-recitations
+        name: Poeta Ex Machina 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