End of training

README.md

@@ -5,9 +5,24 @@ tags:
 - generated_from_trainer
 datasets:
 - transcribed_calls
+metrics:
+- wer
 model-index:
 - name: wav2vec2-base-wonders-phonemes
-  results: []
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: transcribed_calls
+      type: transcribed_calls
+      config: default
+      split: None
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.15521933166430826
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -16,6 +31,9 @@ should probably proofread and complete it, then remove this comment. -->
 # wav2vec2-base-wonders-phonemes
 
 This model is a fine-tuned version of [mattbonnell/wav2vec2-base-wonders-phonemes](https://huggingface.co/mattbonnell/wav2vec2-base-wonders-phonemes) on the transcribed_calls dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8215
+- Wer: 0.1552
 
 ## Model description
 
@@ -35,21 +53,83 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.0001
-- train_batch_size: 64
+- train_batch_size: 128
 - eval_batch_size: 2
 - seed: 42
 - distributed_type: multi-GPU
 - num_devices: 4
-- total_train_batch_size: 256
+- total_train_batch_size: 512
 - total_eval_batch_size: 8
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.01
-- num_epochs: 10
+- num_epochs: 3000
 - mixed_precision_training: Native AMP
 
 ### Training results
 
+| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
+|:-------------:|:------:|:-----:|:---------------:|:------:|
+| 0.0025        | 50.0   | 500   | 0.7040          | 0.1589 |
+| 0.0017        | 100.0  | 1000  | 0.7759          | 0.1549 |
+| 0.0014        | 150.0  | 1500  | 0.7451          | 0.1576 |
+| 0.0019        | 200.0  | 2000  | 0.7775          | 0.1596 |
+| 0.0022        | 250.0  | 2500  | 0.7332          | 0.1626 |
+| 0.0018        | 300.0  | 3000  | 0.7833          | 0.1585 |
+| 0.0016        | 350.0  | 3500  | 0.7756          | 0.1553 |
+| 0.0016        | 400.0  | 4000  | 0.7216          | 0.1610 |
+| 0.0019        | 450.0  | 4500  | 0.7868          | 0.1578 |
+| 0.0012        | 500.0  | 5000  | 0.7815          | 0.1567 |
+| 0.0021        | 550.0  | 5500  | 0.6860          | 0.1570 |
+| 0.0014        | 600.0  | 6000  | 0.7580          | 0.1573 |
+| 0.0014        | 650.0  | 6500  | 0.7352          | 0.1583 |
+| 0.0016        | 700.0  | 7000  | 0.7849          | 0.1569 |
+| 0.0016        | 750.0  | 7500  | 0.7794          | 0.1583 |
+| 0.0012        | 800.0  | 8000  | 0.7791          | 0.1573 |
+| 0.0012        | 850.0  | 8500  | 0.7973          | 0.1571 |
+| 0.001         | 900.0  | 9000  | 0.7465          | 0.1551 |
+| 0.0019        | 950.0  | 9500  | 0.8304          | 0.1587 |
+| 0.0009        | 1000.0 | 10000 | 0.7757          | 0.1579 |
+| 0.0013        | 1050.0 | 10500 | 0.7556          | 0.1586 |
+| 0.0009        | 1100.0 | 11000 | 0.7624          | 0.1566 |
+| 0.0009        | 1150.0 | 11500 | 0.7917          | 0.1566 |
+| 0.0013        | 1200.0 | 12000 | 0.7550          | 0.1598 |
+| 0.0009        | 1250.0 | 12500 | 0.7517          | 0.1555 |
+| 0.0015        | 1300.0 | 13000 | 0.7491          | 0.1586 |
+| 0.0013        | 1350.0 | 13500 | 0.8027          | 0.1594 |
+| 0.0014        | 1400.0 | 14000 | 0.7748          | 0.1577 |
+| 0.0015        | 1450.0 | 14500 | 0.6983          | 0.1587 |
+| 0.0009        | 1500.0 | 15000 | 0.7734          | 0.1583 |
+| 0.001         | 1550.0 | 15500 | 0.7885          | 0.1570 |
+| 0.0009        | 1600.0 | 16000 | 0.7818          | 0.1577 |
+| 0.0009        | 1650.0 | 16500 | 0.8128          | 0.1559 |
+| 0.0008        | 1700.0 | 17000 | 0.7904          | 0.1554 |
+| 0.0011        | 1750.0 | 17500 | 0.7784          | 0.1587 |
+| 0.0009        | 1800.0 | 18000 | 0.7910          | 0.1585 |
+| 0.0011        | 1850.0 | 18500 | 0.7434          | 0.1570 |
+| 0.001         | 1900.0 | 19000 | 0.7241          | 0.1562 |
+| 0.0007        | 1950.0 | 19500 | 0.8213          | 0.1541 |
+| 0.0008        | 2000.0 | 20000 | 0.7713          | 0.1541 |
+| 0.0008        | 2050.0 | 20500 | 0.8151          | 0.1542 |
+| 0.0007        | 2100.0 | 21000 | 0.7770          | 0.1557 |
+| 0.0006        | 2150.0 | 21500 | 0.8487          | 0.1553 |
+| 0.0007        | 2200.0 | 22000 | 0.8332          | 0.1550 |
+| 0.0007        | 2250.0 | 22500 | 0.7931          | 0.1559 |
+| 0.0006        | 2300.0 | 23000 | 0.8252          | 0.1552 |
+| 0.0006        | 2350.0 | 23500 | 0.8609          | 0.1543 |
+| 0.0005        | 2400.0 | 24000 | 0.8398          | 0.1543 |
+| 0.0006        | 2450.0 | 24500 | 0.7921          | 0.1535 |
+| 0.0006        | 2500.0 | 25000 | 0.8223          | 0.1552 |
+| 0.0006        | 2550.0 | 25500 | 0.7902          | 0.1561 |
+| 0.0005        | 2600.0 | 26000 | 0.7974          | 0.1564 |
+| 0.0007        | 2650.0 | 26500 | 0.7761          | 0.1556 |
+| 0.0004        | 2700.0 | 27000 | 0.8105          | 0.1548 |
+| 0.0004        | 2750.0 | 27500 | 0.7826          | 0.1542 |
+| 0.0003        | 2800.0 | 28000 | 0.8056          | 0.1551 |
+| 0.0004        | 2850.0 | 28500 | 0.7956          | 0.1534 |
+| 0.0005        | 2900.0 | 29000 | 0.8316          | 0.1544 |
+| 0.0004        | 2950.0 | 29500 | 0.8164          | 0.1545 |
+| 0.0005        | 3000.0 | 30000 | 0.8215          | 0.1552 |
 
 
 ### Framework versions

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:034af7fe7d8de55106c5ab1c9a3bfad15c9e7c1a5d18e08b3e71115cd7828937
+oid sha256:4cebe60e657c051201065e239b65564c51385efe223a52622e99a9e1cface71e
 size 188841430