End of training

README.md

@@ -6,8 +6,9 @@ base_model: openai/whisper-tiny
 tags:
 - generated_from_trainer
 datasets:
-- deepdml/igbo-dict-expansion-16khz
 - deepdml/igbo-dict-16khz
+- google/fleurs
+- deepdml/igbo-dict-expansion-16khz
 metrics:
 - wer
 model-index:
@@ -18,15 +19,16 @@ model-index:
       type: automatic-speech-recognition
     dataset:
       name: google/fleurs
-      type: deepdml/igbo-dict-expansion-16khz
+      type: deepdml/igbo-dict-16khz
       config: ig_ng
       split: test
       args: ig_ng
     metrics:
     - name: Wer
       type: wer
-      value: 89.15504591613625
+      value: 60.390651571838106
 ---
+
 <!-- 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. -->
 
@@ -34,9 +36,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the google/fleurs dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.8423
-- Wer: 89.1550
-- Cer: 51.2543
+- Loss: 1.2453
+- Wer: 60.3907
+- Cer: 25.7029
 
 ## Model description
 
@@ -66,13 +68,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch   | Step | Validation Loss | Wer     | Cer     |
-|:-------------:|:-------:|:----:|:---------------:|:-------:|:-------:|
-| 0.2126        | 2.0344  | 1000 | 3.7178          | 86.3321 | 49.8998 |
-| 0.1179        | 4.0688  | 2000 | 2.8735          | 87.9452 | 52.9006 |
-| 0.0729        | 7.0204  | 3000 | 2.6541          | 86.7208 | 50.7179 |
-| 0.0519        | 9.0548  | 4000 | 2.7895          | 89.4806 | 51.4953 |
-| 0.0331        | 12.0064 | 5000 | 2.8423          | 89.1550 | 51.2543 |
+| Training Loss | Epoch  | Step | Validation Loss | Wer     | Cer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|:-------:|
+| 0.2001        | 1.0406 | 1000 | 0.9724          | 58.8455 | 24.7463 |
+| 0.0942        | 2.0812 | 2000 | 1.0967          | 60.7065 | 24.6946 |
+| 0.0633        | 3.1218 | 3000 | 1.1767          | 59.6472 | 24.2311 |
+| 0.0417        | 5.003  | 4000 | 1.2294          | 60.0262 | 25.0141 |
+| 0.0392        | 6.0436 | 5000 | 1.2453          | 60.3907 | 25.7029 |
 
 
 ### Framework versions
@@ -81,16 +83,3 @@ The following hyperparameters were used during training:
 - Pytorch 2.3.0+cu121
 - Datasets 2.19.1
 - Tokenizers 0.19.1
-
-## Citation
-
-Please cite the model using the following BibTeX entry:
-
-```bibtex
-@misc{deepdml/whisper-tiny-ig-mix-norm,
-      title={Fine-tuned Whisper tiny ASR model for speech recognition in Lingala},
-      author={Jimenez, David},
-      howpublished={\url{https://huggingface.co/deepdml/whisper-tiny-ig-mix-norm}},
-      year={2025}
-    }
-```

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a6e4dabcc254f3e609a134053fc43552bd37719ad8cdef7d000934a488ce667a
+oid sha256:452cff349f66ba11fa450cb629f8f8347c93861288c69b78b7f7a9d322e8b1ce
 size 151061672