Fix output labels for AudioFlamingo3 (and related) models
Author: ebezzam
Pull request: yes

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# What does this PR do?

Fix bug in prepared output labels, as mentioned [here](https://github.com/huggingface/transformers/pull/47111/changes#r3529962850), after [this refactor](https://github.com/huggingface/transformers/pull/45493) I think?

Script comparing before/after fix
```python
from transformers import AudioFlamingo3ForConditionalGeneration, AutoProcessor


model_id = "nvidia/audio-flamingo-3-hf"
processor = AutoProcessor.from_pretrained(model_id)
model = AudioFlamingo3ForConditionalGeneration.from_pretrained(model_id, device_map="auto")
model.train()

conversation = [
    [
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Transcribe the input speech."},
                {
                    "type": "audio",
                    "path": "https://huggingface.co/datasets/nvidia/AudioSkills/resolve/main/assets/WhDJDIviAOg_120_10.mp3",
                },
            ],
        },
        {
            "role": "assistant",
            "content": [
                {
                    "type": "text",
                    "text": "The transcription of the audio is 'summer follows spring the days grow longer and the nights are warm'.",
                }
            ],
        },
    ],
    [
        {
            "role": "user",
            "content": [
                {
                    "type": "text",
                    "text": "This track feels really peaceful and introspective. What elements make it feel so calming and meditative?",
                },
                {
                    "type": "audio",
                    "path": "https://huggingface.co/datasets/nvidia/AudioSkills/resolve/main/assets/FPSbCAANfbJLVSwD.mp3",
                },
            ],
        },
        {
            "role": "assistant",
            "content": [
                {"type": "text", "text": "The transcription of the audio is 'some transcription of the audio'."}
            ],
        },
    ],
]

inputs = processor.apply_chat_template(
    conversation,
    tokenize=True,
    add_generation_prompt=True,
    return_dict=True,
    processor_kwargs={"output_labels": True},
).to(model.device, dtype=model.dtype)

# What the model is actually trained to predict: decode the unmasked label positions
for i, labels in enumerate(inputs["labels"]):
    print(f"Labels {i}:", repr(processor.tokenizer.decode(labels[labels != -100])))

loss = model(**inputs).loss
loss.backward()
print("Loss:", loss.item())


"""
BEFORE

Labels 0: '!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!'
Labels 1: '!!!!!!!!!!!!!!$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!'
Loss: 14.966017723083496

AFTER

Labels 0: "
system\nYou are a helpful assistant.
\n
user\nTranscribe the input speech.
\n
assistant\nThe transcription of the audio is 'summer follows spring the days grow longer and the nights are warm'.
\n
assistant\n"
Labels 1: "
system\nYou are a helpful assistant.
\n
user\nThis track feels really peaceful and introspective. What elements make it feel so calming and meditative?
\n
assistant\nThe transcription of the audio is 'some transcription of the audio'.
\n
assistant\n"
Loss: 5.149610996246338

"""

```

Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_47112). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

should we add a test in processor tester?  would be nice so we can catch bugs early on

**[For maintainers]** Suggested jobs to run (before merge)

run-slow: audioflamingo3, glmasr, musicflamingo

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### CI recap

**Dashboard:** [View test results in Grafana](https://transformers-ci.lor-e.huggingface.cool/d/pytest-observability-by-pr/pytest-observability-branch?var-pr=47112)
**Latest run:** [28810434165:1](https://github.com/huggingface/transformers/actions/runs/28871003407)
**Result:** `success` | **Jobs:** 3 | **Tests:** 152 | **Failures:** 0 | **Duration:** 7m 35s

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